NUREG/CR-6778

The Effects of Composition andHeat Treatment on Hardening andEmbrittlement of Reactor PressureVessel Steels

University of California at Santa Barbara

U.S. Nuclear Regulatory CommissionOffice of Nuclear Regulatory ResearchWashington, DC 20555-0001

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NUREG/CR-6778

The Effects of Composition andHeat Treatment on Hardening andEmbrittlement of Reactor PressureVessel Steels

Manuscript Completed: April 2002Date Published: May 2003

Prepared byG. R. Odette, G. E. Lucas, D. Klingensmith,B. D. Wirth, D. Gragg

Department of Mechanical and Environmental EngineeringUniversity of California at Santa BarbaraSanta Barbara, CA 93106

C. Santos, NRC Project Manager

Prepared forDivision of Engineering TechnologyOffice of Nuclear Regulatory ResearchU.S. Nuclear Regulatory CommissionWashington, DC 20555-0001NRC Job Code Y6396

NUREG/CR-6778, has been reproducedfrom the best available copy.

ABSTRACT

This report addresses several important issues regarding possible revisions of RG 1.99 Rev. 2 topredict irradiation induced hardening (Aay) and hence embrittlement manifested as shifts (AT) in the41 J Charpy test transition temperature. We are developing a Aa, database from controlled, single-variable experiments to map the individual and interactive effects of metallurgical and environmentalvariables. The data are generated from a large matrix of composition-controlled alloys irradiated inthe Irradiation Variables Facility (IVAR) at the University of Michigan Ford Research Reactor. Theresults provide quantitative and independent validation of the two component form of theNUREG/CR-655 1 model, comprised of matrix feature (MF) and copper rich precipitate (CRP) terms.The IVAR database also quantitatively supports: 1) the model treatments of a strong copper-nickelinteraction in the CRP term; 2) the treatment of phosphorous in the MF term; 3) an independentvalidation of a maximum effective matrix copper level (Cu.) of around 0.3% following heattreatment; and 4) a sensitivity of Cu. to nickel content. The IVAR database also shows: I)manganese interaction with copper and nickel in the CRP contribution; 2) manganese and nickelincrease the MF term; 3) a somewhat unanticipated effect of flux and flux-composition interactionson the fluence dependence of Aay and AT; and 4) a possible reduction in the effect of phosphorus athigher copper.

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TABLE OF CONTENTS

ABSTRACT ........................... iii

LIST OF FIGURES .......................... vii

LIST OF TABLES .......................... ix

EXECUTIVE SUMMARY ........................... x

ACKNOWLEDGMENTS ........................... xii

NOMENCLATURE AND SYMBOLS ........... ............... xiii

I BACKGROUND AND INTRODUCTION .1

2 OBJECTIVES, STRATEGY, FOCUS AND ORGANIZATION OF THE REPORT . 4

3 MATERIALS, EXPERIMENTAL METHODS AND DATA ANALYSIS ANDEVALUATION PROCEDURE .6

3.1 Alloys And Specimens .63.2 Irradiations 73.3 Tensile Testing .183.4 Small Angle Neutron Scattering .193.5 Field Emission Gun Scanning Transnission Electron Microscopy .213.6 Electrical Resistivity Measurements .223.7 Seebeck Coefficient Measurements .23

4 EFFECTS OF COMPOSITION ON IRRADIATION HARDENING ANDEMBRITTLEMENT .24

4.1 Summary of the Data Trends .. 244.1.1 Copper Bearing Alloys .244.1.2 Low Copper Alloys .28

5 ANALYSIS OF THE COMPOSITIONAL TRENDS .33

5.1 Comparison of the IVAR Results With Predictions of theNUREG/CR-6551 Model .. 33

5.2 The Microstructural Basis, Mechanisms and Models for the CompositionDependence of Hardening and Embrittlement .. 365.2.1 Copper Rich Precipitates .365.2.2 Matrix Features .39

5.3 Discussion of Improvements in the NUREG EmbrittlementCorrelation Model Treatment of Composition Effects . .40

6 EVALUATION OF THE MATRIX COPPER CONTENT .44

6.1 General Effects of Heat Treatment on 0 y and y . . .456.2 Estimates of Matrix Copper Levels 49

6.2.1 Estimates of Cum Based on Dsy Deviations From the Low Copper cTrend Line .49

6.2.2 Estimates of Cum Based on VSR AcFy Trends and the ModifiedNUREG/CR-6551 Aay Model .52

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6.3 Microanalytical Assessments of Cum ..................................................... 586.3.1 Field Emission Gun Scanning Transmission Electron Microscopy ................. 586.3.2 Electrical Resistivity ..................................................... 586.3.3 Seebeck Coefficient ..................................................... 62

6.4 Summary and Discussion of the Dsy and Microanalytical Based Estimatesof CUm ................ 65

6.5 Small Angle Neutron Scattering Studies from the PB Experiment .............................. 66

7 A PRE-PRECIPlTATION MODEL FOR Cu ................................ 71

8 SUMMARY AND CONCLUSIONS ............................... 74

9 REFERENCES ............................... 76

APPENDIX A THE NUREG A, MODEL .. 80

APPENDIX B TENSILE DATA FOR T4, T14, VSR AND PB . .85

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LIST OF FIGURES

Figure Page

Figure 3-1 Specimen Baskets in the IVAR Facility ............................................................. 13

Figure 3-2 Schematic Design of the IVAR Irradiation Facility ................................................... 14

Figure 4-1 Variation of Auy with bulk copper in intermediate nickel alloys for the a) CM andb) LV series ............................................................. 25

Figure 4-2 Variation of Aa. with nickel for a) 0.4 copper and b) 0.2 copper CM alloys;c) comparison of Au, versus nickel for intermediate and high copper steels for T14;d) Variation of AcY with nickel for high copper LV series steels (corresponding CMalloys shown for comparison as small filled symbols) ........................... ................... 26

Figure 4-3 Variation of y with manganese for intermediate nickel, high copper CM and LVsteels ............................................................. 27

Figure 4-4 Variation of boy with boron, molybdenum, and chromium for a) PB and b) T14 ... 27

Figure 4-5 Variation of Au with phosphorous for a) low copper, low nickel; b) low copper,intermediate niclel; and c) low copper, high nickel steels; d) Variation of phosphoroussensitivity (B) with nickel; e) Comparison of Aay (P) for alloys with 0.02 and 0.11copper ............................................................. 30

Figure 4-6 Variation of Ac, with nickel for a) low and b) high phosphorous steels .......... .......... 31

Figure 4-7 Variation of Aay with manganese for low copper CM alloys ................ .................... 31

Figure 4-8 Variation of Aar with carbon, nitrogen, boron and tramp elements (TE) for low copperCM steels ............................................................. 32

Figure 5-1 Comparison of the NUREG-Acry model predictions with the data from thecapsule T14 ............................................................. 34

Figure 5-2 Comparison of the NUREG-Ac7 model predictions with the data from capsule T14adjusted to 0.8% nickel and 0.005% phosphorous .................................................. 34

Figure 5-3 Comparison of the NUREG-AcTy model predictions of nickel dependence ofembrittlement with the T14 data for a) 0.4% copper and b) 0.2% copper steels ....... 35

Figure 54 Comparison of NUREG-A&, model predictions with AG data as a function of fluencefor low copper (0.02%) intermediate nickel (0.85%) CM alloys for both low(0.005%, CM3) and high (0.04%, CM5) phosphorous levels ............... .................... 35

Figure 5-5 Volume fraction of CRP's estimated from SANS measurements on CM and LValloy for the PB capsule as a function of a) nickel for CM alloys, b) nickel forLV alloys, and c) manganese for CM alloys; d) comparison of measured AaSJ withvalues predicted from SANS microstructural parameters ................... ..................... 38

Figure 5-6 Variation of Aa, with a matrix chemistry factor given in Equation 5-2 for low copperCM and LV steels for capsules T14 and PB. The unalloyed VM steels are shownas filled triangles ............................................................. 42

Figure 5-7 Acy for various V-series alloys with no copper irradiated in PB ............ ................ 43

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Figure 5-8 a) Comparison of NUREG matrix feature predictions with low copper French powerreactor surveillance data; b) plot showing scatter in Aca, in low copper steelirradiations in this study and unexplained differences between CM and LV alloys .... 43

Figure6-1 VariationofcywithPTfora)CM5, 11, 18b)CM3, 11, 19c)CM12, 13,20 ............ 47

Figure 6-2 Variation of Acr, with y, (unirradiated) for a) high (0.42%) copper CM alloys,b) intermediate (0.8%) nickel 0.22% copper alloys ................................................. 48

Figure 6-3 Variation of Aa, with c for irradiated intermediate nickel alloys ............. ................. 48

Figure 6-4 Variation of Aa with c for intermediate nickel CM and LV alloys in capsules T14(a and b), T4 (c and d) and PB (e andf) .......................................................... 51

Figure 6-5 Variation of Ac with SR condition for a) CM3, b) CM5, c) CMII, d) CM12,e) CM13, f) C?I16, g) CM18, h) CMI9, i) CM 20 ................................................... 53

Figure 6-6 Aa, -based NUREG model prediction of the variation in Cum with SR time forthe VSR data for a) CM] 1, b) CMI2, c) CMI8, d) CM 19, e) CM20; f) Comparisonof high copper CM]9 to two lower Cu steels ......................................................... 56

Figure 6-7 Aa, -based NUREG model prediction of the variation in Cum with stress relieftime for the PB data for CM12, CMI8, CM 19, CM20 .............................................. 57

Figure 6-8 Idealized variation of resistivity with content C. of solute x ................. .................... 60

Figure 6-9 Variation of resistivity with copper content for a range of alloys ............. ................ 61

Figure 6-10 Variation of resistivity with copper content for a) CM, b) LV and c) as-temperedCM alloys ............................................................. 63

Figure 6-11 Variation of Seebeck coefficient with copper content .64

Figure 6-12 Variation of Seebeck coefficient with copper content for a) stress-relieved CM,b) as-tempered CM and c) LV-series alloys .68

Figure 6-13 Cum measurements from various techniques for a) CMI I, b) CM19, c) LC .69

Figure 6-14 Effects of tr on CRP features as measured by SANS on CM19 from the PBcapsule .70

Figure 7-1 Comparison of Cur to Cum for high copper CM alloys from VSR .72

Figure 7-2 Comparison of Cum from VSR data to predictions of Equations 7-2 through 7-4 .... 73

Figure 7-3 Comparison of Cum for CMI9 as a function of tr .73

Figure A-I Variation of Cc with AT. The dashed line shows the average .83

Figure A-2 Comparison measured Ao, with values predicted from NUREG model for T4 . 83

Figure A-3 Variation of the difference between predicted and measured Ac, with nickel . 84

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LIST OF TABLES

Table Page

Table 3-1 CM-Series Alloy Compositions and Heat Treatments ................................................ 8

Table 3-2 Stress Relief Anneal Matrix .......................................................... 9

Table 3-3 LV-Series Alloy Compositions and Heat Treatments ................................................. 9

Table 3-4 Commercial Steels ......................................................... 10

Table 3-5 VM-Series Alloy Composition ......................................................... 11

Table 3-6 Specimen Loadings for Capsules T4 and T14 ......................................................... 15

Table 3-7 Capsule loading for VSR ......................................................... 16

Table 3-8 Capsule loading for PB ......................................................... 17

Table 3-9 Irradiation Conditions ......................................................... 19

Table 4-I Summary of Compositional Dependence of Hardening in High Copper Steels ........ 29

Table 4-2 Summary of Compositional Dependence of Hardening in Low Copper Steels ........ 32

Table 6-1 Estimated Cum for Intermediate Nickel High Copper CM Alloys in VSR Study ....... 50

Table 6-2 Estimated Cum for Intermediate Nickel High Copper CM Alloys in VariousCapsules ......................................................... 50

Table 6-3 Estimated Cum for High Copper CM Alloys in VSR Study ................... ................... 57

Table 6-4 Estimated Cum for High Copper CM Alloys in PB Study ................... .................... 57

Table 6-5 Averaged Cum Following Heat Treatment at -590-610C ....................................... 58

Table 6-6 FEGSTEM Estimates of Cu,, for CM12, CM19 and CM20 ................... ................... 59

Table 6-7 Least Square Fit Calibration of Equations 6-7 and 6-8 ....................................... ,.64

Table 6-8 Microanalytical and Afl Based Estimates of Cum for Typical As-tempered andStress-relieved Conditions ...................................... 67

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EXECUTIVE SUMMARY

Safe operation of reactor pressure vessels requires evaluation of irradiation embrittlement by neutronsleaking from the core. Embrittlement is currently monitored by measuring changes in the energy-temperature curves of Charpy V-notch specimens irradiated in reactor surveillance programs.Embrittlement is characterized in terms of reductions in the Charpy upper shelf energy (AUSE) andelevations of the temperature at 41J (AT). The latter is the focus of this report. Prescriptions forevaluating AT (and AUSE) for a particular steel and vessel exposure condition are provided in USNRC Regulatory Guide 1.99 Revision 2 (RG 1.99/2). However, RG 1.99/2 was based on a rathersmall database, assembled from the literature several years earlier, and reflects the limitedunderstanding of embrittlement mechanisms at that time.

Over the intervening years, both fundamental understanding of embrittlement mechanisms and thesurveillance database have grown, along with a recognition that complex interactions between theirradiation and metallurgical variables control AT. Thus the synthesis of various sources ofinformation is the key to reliable embrittlement predictions. Recently a new AT correlation modelwas developed based on statistical fits to the power reactor embritdement database (PREDB), usingequations that were both developed and vetted using physical models and independent sources ofpertinent data. The NUREG/CR-6551 Model (sometimes known as the Eason-Wright-Odette Model)has been extensively scrutinized by the nuclear industry and researchers around the world. TheASTM Subcommittee El 0.02 has led the independent evaluation of this work, and has considered theNUREG model as a candidate for adoption for AT predictions in draft standard E900. The NUREGmodel, and its progeny, are also under consideration for adoption in a preposed revision to RG1.99/2.

The NUREG model has proven to be rather robust in these evaluations. It represents a significantstatistical improvement over RG 1.99/2, and is based on a much better physical model ofembrittlement. However specific issues have been raised, and new questions continue to emergeregarding details of the model. The results presented in this report represent part of a larger overalleffort to address and resolve these issues. The technical approach involves developing anindependent embrittlement database from controlled, single-variable experiments. High-resolutionexperimental maps of the individual and interactive effects of metallurgical and environmentalvariables on embrittlement are derived from irradiation and post-irradiation testing of very largeexperimental matrices. These studies take advantage of the relationship between AT and increases inyield stress (Aay), which can be measured using small tensile specimens. These studies achieveprecise control and characterization of the embrittlement variables. Irradiations are carried out in theIrradiation Variable Facility (IVAR) at the University of Michigan Ford Research Reactor. he largeexperimental hsy database under development, will be complemented by an extensive effort tocharacterize the micro(nano)structural changes responsible for Acy and AT. The collective resultswill be analyzed and used to develop quantitative, mechanism-based embrittlement models.

This report focuses on a subset of important questions that must be answered in establishing atechnical basis for any future revision to RG 1.99/2. In particular the following issues are addressed,and to a large extent resolved, by the VAR data and analysis reported here. These advances include:

1. Quantitative independent validation of the general two component form of the NUREG modelcomprised of copper-independent matrix features and copper-dependent copper rich precipitates(CRPs) terms.

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2. Quantitative independent validation of the very strong interaction between copper and nickel inthe NUREG model CRP contribution to AT. The specific thermodynamic basis for this interactionis described, along with an example from a larger supporting microstructural characterizationdatabase.

3. Validation of the inclusion of phosphorous in the NUREG model, and strong support for itsapproximate treatment in the matrix feature contribution to AT.

4. Validation of a maximum effective matrix copper level of around 0.3% following tempering andstress relief heat treatments as found in the NUREG model. Strong support is also presented foreven lower maximum effective matrix copper levels of about 0.25% in low-to-intermediate nickelsteels, as well as evidence for corresponding levels in excess of 0.3% in high nickel steels. Therole of stress relief time and temperature on effective matrix copper levels is also elucidated andrepresented in terms of a simple pre-precipitation model.

In addition, the database and analysis in this report also provides additional insight into several otherissues, which are further from closure. Resolution of these issues could lead to significant furtherimprovements in embrittlement forecasting. They include:

I. Possible sources of product form variability and data scatter in the CRP term. These includeembrittlement contributions from elements not explicitly accounted for in the NUREG model, likemanganese (interacting with nickel and copper), and effects of microstructural variations on thefluence dependence of Acy and AT.

2. An unanticipated effect of flux and flux-composition interactions on the fluence dependence ofthe CRP contribution to A;y and AT.

3. Effects of the unirradiated constitutive and Charpy properties on: a) the A&CF produced by aspecified embrittlement microstructure; and b) the relationship between A(y and AT. This workhas also identified new mechanisms that influence the effects the heat treatment on theunirradiated microstructure and properties, hence, also on AGy and AT.

4. Possible sources of product form variability and data scatter in the matrix feature term, includingan increase in Acy with manganese and nickel.

5. A possible interaction reducing the effect of phosphorus at higher copper.

All of these issues, and several others, are the subject of ongoing research in the UCSB program.

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ACKNOWLEDGMENTS

The authors appreciate the advice and encouragement of Al Taboada, and Mike Vassilaros ourformer project managers at the U. S. Nuclear Regulatory Commission and Carolyn Fairbanks ourcurrent project manager. Al Taboada contributed enormously to the conceptual design of ourprogram and Mike Vassilaros was instrumental in tuming these concepts into realities. CarolynFairbanks has helped us in the completion of this part of the work and has provided sustained supportfor our research. The advice and support from other U.S. NRC staff are also appreciated. The staffand students in our group at the University of California Santa Barbara, particularly Chris Cowan,have made important contributions to various parts of this research. The support of the collaboratorsat ORNL, particularly Roger Stoller, Randy Nanstad, Mikhail Sokolov and Dennis Heatherly, as wellas the staff at the Ford Nuclear Reactor irradiation facility, particularly Phil Simpson, are greatlyappreciated. We would also like thank the staff at AEA Technology, especially Amanada Kenway-Jackson, Colin English and Will Phythian, for their role in procuring alloys and performingFEGSTEM studies. The work was performed under U.S. NRC Contract 04-94-049.

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NOMENCLATURE AND SYMBOLS

SYMBOLS

Ai intercept of Acry sensitivity to ith specieBi slope of Acy sensitivity to ith specieCc ratio of AT to AayCF chemistry factorC1 concentration of ith specieCubk bulk copper concentrationCue effective copper concentrationCum matrix copper concentrationEsr pre-precipitation effective activation energyF neutron scattering factorfi volume fraction of ith specief0 flux factorki resistivity coefficient of ith speciek,r pre-precipitation rate coefficientNi number density of ith featurePrt heat treatment temperature-time factorq neutron scattering vectorr radius of ith featurerip radius of ith feature at peak strengthrm mean radius of scattering featureS Seebeck coefficientSi Seebeck coefficient from ith contributiontht heat treatment timetsr stress relief timeTht heat treatment temperatureAT 41J indexed Charpy transition temperature shiftAT3 shift due to ith contributionVj Volume of ith feature

0 scattering distribution fit parameterx NUREG copper factor* flux

fluenceOs neutron scattering angle relative to magnetic fieldYsr numerical constant for pre-precipitation ratesKi Seebeck coefficient sensitivity to ith speciesAi strength of ith obstaclep ResistivityPi contribution to resistivity of ith sourceA p neutron scattering contrastd/dSd SANS scattering intensitya,i strength contribution from ith source<su unirradiated obstacle yield strength contributionay yield strengthAaY change in yield strengthe superposition parameter

ASAXS Anomalous Small Angle X-ray ScatteringCRP Copper rich precipitate

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FEGSTEM Field Emission Gun Scanning Transmission ElectronMicroscope

FNR Ford Nuclear ReactorHF High FluxHT Heat TreatmentIVAR Irradiation Variables FacilityIF Intermediate FluxLF Low FluxPIA Post-Irradiation AnnealingSAW Submerged Arc WeldSR Stress ReliefSSR Standard Stress ReliefSANS Small Angle Neutron ScatteringTEP Thermoelectric Power

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1 BACKGROUND AND INTRODUCTION

Accurate prediction of neutron irradiationembrittlement of reactor pressure vessels is a keycomponent in structural integrity assessments forboth normal operation and during accidenttransients [USNRC, 19861. Embrittlement iscurrently empirically characterized in reactorsurveillance programs by measuring changes inthe Charpy V-notch transition energy-temperature curves of representative vessel steels.Data from surveillance programs are archived inthe Power Reactor Engineering Data Base(PREDB) [Stallman et. al, 1994], compiled atOak Ridge National Laboratory. Charpy dataare usually represented as temperature shiftsindexed at 41J (AT) and reductions in the uppershelf energy (USE). Regulatory procedures forpredicting embrittlement are described in USNRC Regulatory Guide 1.99 Revision 2 (RG1.99/2) published in 1988 [USNRC, 1988].However, the AUSE and AT in RG 1.99/2 werebased on a rather small database, assembledfrom the literature several years earlier andreflect the limited understanding ofembrittlement mechanisms at that time.

Over recent years both fundamentalunderstanding of embrittlement mechanisms andthe surveillance database have grown, along witha recognition that complex interactions betweenthe irradiation and metallurgical variablescontrol AT [Odette and Lucas, 1989, 1996,1997, 1998; Odette, 1998; Buswell and Jones,1993; Fisher and Buswell, 1987; Stoller, 1996;Lott and Freyer; 1996, Bolton, et al, 1996;McElroy and Lowe, 1996; English et al, 1997].The irradiation variables include temperatureand exposure time, neutron flux, fluence andspectrum. Metallurgical variables includecomposition and processing history, whichcombine to mediate the start-of-life alloymicrostructure and microchemistry. Elementsthat are known, or thought, to influence ATinclude copper, nickel, phosphorous, manganese,and perhaps, silicon and nitrogen.Corresponding processing and microstructuralvariables are more difficult to parameterize, butclearly include product form and tempering-

stress relief heat treatment. A myriad of otherfactors, that mediate the start-of-life condition ofa steel, as represented by grain and subgrainstructures, dislocation densities andarrangements, as well as carbide and othersecond phase distributions, also play a role.These microstructural factors are manifested interms of both the effect of the start-of-lifeproperties on embrittlement as well as theireffect on fine scale changes in themicrostructures caused by irradiation that alterthese properties.

An example of such complex metallurgicaleffects, which are the focus of this report, isprovided by the interaction between copper,nickel, manganese and stress-relief heattreatment. Irradiation hardening, which is theprimary cause of embrittlement, increases withincreasing nickel and manganese content.However, the effect of these elements acting intandem, is synergistic in steels containing asignificant amount of copper. Further at highlevels, the effective copper content is influencedby the heat treatment because of pre-precipitation of this element. The amount ofcopper pre-precipitation appears to beinfluenced by the alloy nickel content. Both theheat treatment and composition in turn influencethe start-of-life alloy strength, which also affectsthe irradiation hardening. Additionalcombinations of these variables may influenceAT, but it is sufficient to conclude that suchinteractions and synergisms can only be reliablyunderstood and accounted for based on insightprovided by combinations of careful, singlevariable experiments and modeling. However, itis also equally clear that such complexity, andlimitations in understanding, demand thatpredictive models be derived from the mostrealistic database available, currently representedby the PREDB.

Thus the synthesis of various sources ofinformation is the key to reliable embrittlementpredictions. Recently a major advance inimplementing this paradigm was reported in

I

NUREGICR-6551 [Eason et al, 1988]. whichfeatured the following key elements in derivingAT predictions.

1. The AT predictions were based on non-linearleast squares fits of correlation equations to acarefully scrubbed, frozen version of thePREDB.

2. The correlation equations were developedbased on understanding of key embrittlementmechanisms.

3. Selection from among a large number ofstatistically similar calibrated correlationequations was based on both mechanisticconsiderations and consistency withindependent sources of data, largely derivedfrom test reactor studies.

4. Both the limits of the correlation equations,and the likelihood they would continue to berefined, were recognized. Thus unless therewas a combination of mechanistic andstatistical significance dictating otherwise, thecorrelation equations were kept as simple andwith as few degrees of freedom as possible.The attendant compromises included use ofcorrelation equation forms that wereconsistent with the demands of nonlinear datafitting methods.

While the NUREG/CR-655I equations are fairlyrobust and reliable, more importantly the overallmethodology established a framework forcontinuing improvements in embrittlementpredictions and a basis to assess important gapsin understanding. Significant issues that havebeen identified include:

I. What are the sources of embrittlementvariability associated with product form, oreven vessel vendor, and the correspondingunderlying microstructural basis? Note this isalso an important issue related to othersources of material variability, like weldpractice, heat affected zones, throughthickness variation of properties and, veryimportantly, treatment of the relation of

surveillance materials to those in the vesselitself, or the issue of surrogate materials.

2. What are the sources of large scatter anddifferences with other database trends in thecopper-independent, so-called matrix featureterm?

3. What is the effective upper cut-off in coppercontent; and how is this affected by othervariables, such as nickel and heat treatment,and how is it best modeled in the correlationequations?

4. What is the effect of phosphorous and howcan it be best modeled?

5. What are the effects of flux and time-at-temperature? How are these factorsinfluenced by other variables and how arethey best treated in the correlation equations?

6. What variables, terms and mechanisms couldbe missing from the existing correlationequations? This includes interactions betweenexisting variables as well as variables that arecurrently not accounted for.

The latter point deserves a brief elaboration.Statistical methods, even using simple, non-physical algebraic correlation equations,generally can reasonably fit a database withinexpected scatter and considering other sourcesof uncertainties. However, various terms in suchmodels may be entirely non-physical, simplyacting as surrogates for real physical effects. Putsimply, the fitting model will force itself to workas well as it can independent of the reality ofhow it does it. At least to some extent, thisinvolves replacing something that is missing withsomething that simply works (or, to say itsimply, pushing something in one place popssomething out in another place). Correlationequations with a more solid physical basis suffersimilar limitations if they are not complete anddo not start with a balance of terms that arephysically based. Non-physical correlationscannot be extrapolated and even fail within inapparently valid regime when variable surrogacy

2

breaks down. Clearly, avoiding such trapsrequires developing independent sources of dataand mechanistic understanding, which-is theoverarching goal of the work partially describedin this report.

3

2 OBJECTIVES, STRATEGY, FOCUS ANDORGANIZATION OF THE REPORT

The UCSB embrittlement research program hasa number of objectives ranging from earlywarnings of possible technical surprises, toimproving a broad array of integrity assessmentmethods, such as the tasks in support of themaster curve method [ASTM E1921-97]. Theactivities pertinent to this report relatespecifically to the issues listed at the end of theprevious section, viz. - developing anindependent database involving controlled,single-variable experiments and mechanisticmodels. This effort involves:

I. Developing high resolution experimentalembrittlement maps of the individual andinteractive effects of metallurgical andenvironmental variables. This task involvesirradiation and post-irradiation testing of avery large matrix of alloy/alloy condition-flux-fluence-temperature combinations withprecise control and characterization of theembrittlement variables. The primary facilityis the Irradiation Variable Facility (IVAR) atthe University of Michigan Ford ResearchReactor.

2. Detailed pre and post-irradiation (as well asannealing-reirradiation) microstructuralstudies and focused mechanism experimentsin support of physical model development.

3. Development of detailed multiscaleembrittlement models that quantitatively treatall key variables and variable interactions.

4. Synthesis of these results with other pertinentinformation and ultimate application toimproved embrittlement correlationequations fit to the PREDB.

A key element of the strategy to meet the firstobjective is the use of yield stress changes (Acr,)as a measure of embrittlement (AT). The a,;-AT relation is well established [Odette et. a,1985; Odette and Lucas, 1989]. but will be

further developed and quantified as part of thiswork. The use of Aa, as the key propertyenables establishing the embritttement mapsusing small tensile specimens coupled with semi-automated testing. As a result very largeexperimental matrices are practical. The use ofAasy also has other advantages, such as generallyhigh precision and physical relationships toother measures of embrittlement, such as shiftsin fracture toughness-temperature master curves[Odette and He, 2000, in press]. The resultsreported here are a small part of the much largeroverall study and focus on the specific effects ofcompositional and heat treatment variations onAGry

A wide variety of techniques are being used, incombination, for microstructuralcharacterization and other mechanism studies.Methods include small angle neutron andanomalous x-ray scattering, atom probe,transmission electron microscopy, postirradiation annealing, electrical resistively andthe Seebeck coefficient. These studies areongoing and only limited, and in some casespreliminary, results on small angle neutronscattering, transmission electron microscopy,electrical resistively and the Seebeck coefficientare presented in this report.

Models of the key sub-processes mediatingembrittlement have been developed andextensively used to improve the understandingof the underlying mechanisms as well as toguide and verify correlation modeldevelopment. Integration of these componentsinto a comprehensive quantitative embrittlementmodel is underway. The results of modelingpertinent to interpreting the experimental trendsare summarized briefly in this report, withfurther details presented elsewhere [Odette andLucas, 1997, 1998; Odette, 1998] or in futurepublications and reports.

The report is organized as follows. A descriptionof the steels examined in this study, the

4

experimental test methods and procedures forthe data analysis and evaluation are described inSection 3. The Acy, for two sets (CM and LV) ofsplit melt UCSB alloys and a range of steelsacquired from other programs irradiated tomedium fluence between 0.48 and xO23nm 2

(E > I MeV) are presented in Section 4. Only alimited number of medium fluence capsulestested to date contain complete, or nearlycomplete, matrices of the steels examined in thisprogram. These data are complemented by theresults for a more limited number of key UCSBalloys contained in other medium fluence IVARcapsules. An analysis and evaluation of theseresults is presented in Section 5, by comparingthe AuY data to predictions of the NUREG/CR-6551 model. Section 6 describes the effects ofsystematic variations in stress relief time andtemperature on Ay; for a subset of the UCSBCM alloys. This section includes the results of avariety of characterization techniques used toevaluate the matrix content of dissolved copper,as well as estimates based on the A;,measurements themselves. These results areanalyzed in Section 7 to assess the mechanismsgiving rise to stress relief effects, with particularemphasis on maximum copper limits set by pre-precipitation. Section 8 summarizes the overallresults and presents the main conclusionsderived from this study.

5

3 MATERIALS, EXPERIMENTAL METHODS AND DATAANALYSIS AND EVALUATION PROCEDURES

3.1 Alloys and Specimens

A large set of alloys was investigated in thisstudy. The alloys are classified in four generalcategories:

I. The compositions of a large set of complexA533B-type split melt steels (CM-series) areshown in Table 3-1. A total of 31 variantsaround a base composition were used toevaluate the effects of both: a) combinationsof Cu (0.0 to 0.8%1), Ni (0.0 to 1.6%), Mn(O to 1.6%) and P (0.005 to 0.040%)contents; and b) single variable modificationsof Mo, N, C, B, Al and As/Sn/Sb contents. All31 alloys contained about 0.005%Al and0.25%Si. The alloys were fabricated incollaboration with AEA Technology,Harwell. Chemistries were determined by themanufacturer, and spot checked for severalalloys upon receipt by a combination ofatomic absorption and interstitial elementanalysis. Further verification of chemistriesis planned. For two of the irradiations, T4and T14 (described below), the alloysreceived a base heat treatment consisting ofan austenitization at 900°C for 0.5h, followedby a salt bath quench at 450°C for 10min, anair cool, tempering at 660°C for 4h: air cooland a stress relief anneal at 607'C for 24 h,followed by a slow cool at 8'C/h to 300*C,and a subsequent air cool. This is referred toas the standard stress relief (SSR) heattreatment. The SSR yielded prior austenitegrain sizes of about 50±10 pm andmicrostructures ranging from temperedbainite (most CM alloys) to mixed temperedferrite-bainite. A complete microstructuraldescription for all the alloys will be providedin a future report.

For one of the irradiations, VSR (describedbelow), nine of the alloys received altemate

I Compositions are given in weight per cent, unless statedortherwise

stress relief anneals; the alloys and the stressrelief anneal matrix are shown in Table 3-2.

Finally, for a piggy-back irradiation, PB(described below), the 31 alloys wereirradiated in the as-tempered condition. Inaddition, several of the alloys received thefollowing alternate heat treatments:

CM5: as-tempered plus aged 480 for100 h, air cooled

CM8: salt bath quenched at 4000C afteraustenitization, then tempered

CM12: as-tempered plus stress relieved600'C 8 h, air cooled

CM18: as-tempered plus stress relieved6000C 40h, air cooled

CMI9: as-tempered plus stress relieved600'C 8, 40 and 80 h, air cooled

CM 19: salt bath quenched at 500'C afteraustenitization, then tempered

CM20: as-tempered plus stress relieved600'C 40h, air cooled

CM20: salt bath quenched at 500C afteraustenitization, then tempered

CM23: salt bath quenched at 400C afteraustenitization, then tempered

CM26: as-tempered plus aged 480' for100 h, air cooled

2. The compositions and heat treatment for aset of eight complex commercial typebainitic model steels (LV-series) withsystematic variations in copper and nickel areshown in Table 3-3. These steels have beenirradiated in previous programs at a variety

6

of conditions, primarily around 300°C,. andare described in more detail elsewhere[Odette and Lucas, 1989]. They havemicrostructures and unirradiated propertiesvery similar to those in the CM-series.

3. The compositions and heat treatments for aset of 13 commercial steels are shown inTable 3-4. The commercial steel seriesconsists of: ) three welds (A, B, C) obtainedfrom Babcock and Wilcox, with a range ofcopper contents from low (0.06) to high(0.28), 2) a set of 5 welds (62W-73W)prepared for and used in the HSSI program;3) plate 02 of the A533B correlation monitormaterial prepared for the HSST program; 4)JRQ plate material developed for an IAEAcoordinated research program; and 5) aLinde 0091 weld (EPRI C) prepared for andused in previous EPRI-sponsored research.Both baseline and irradiated data have beenobtained for all these steels and are largelyreported in the literature. The heattreatments and compositions reported inTable 3-4 were taken from the literature ordocumentation supplied with the plate (e.g.,JRQ).

4. The compositions and heat treatment for a setof 18 simple split melt model iron and steelalloys (VM-series) with systematic variationsin Cu, C, and N are shown in Table 3-5.These alloys were also fabricated incollaboration with AEA Technology,Harwell. Chemistries were determined by themanufacturer, and spot checked for severalalloys upon receipt by a combination ofatomic absorption and interstitial elementanalysis. Further verification of chemistriesis planned. The microstructures of thesealloys are generally characterized by a widedistribution of ferrite grain sizes (in somecases duplex and/or with processing texture).A complete microstructural description forall the alloys will be provided in a futurereport. Rapid quenchingwas carried out tomaintain copper in solution. These alloyswere used in this study to calibrate resistivityand Seebeck coefficients as a function of

copper concentration as discussed in Section6. In addition, several of the alloys wereirradiated in the PB and several other IVARcapsules. However, only a limited numberhave been tested and are reported here.

Sheet tensile specimens with a gage section 9mm x 2 mm x 0.5 mm were prepared byprecision die punching heat treated couponslapped to 0.5±0.005 mm thick. The quality ofthe die was monitored by punching and tensiletesting a variety of calibration metals after aboutevery 500 specimens had been punched.Baseline tensile tests on unirradiated materialindicated some variability in properties in severalof the alloys. Hence, to reduce scatter in thesubsequent yield stress change measurements,the end tabs of selected tensile specimens werepre-indented to obtain Vickers microhardnessnumbers. An average of 4 indentations weremade on the tab ends of the tensile specimens.The microhardness values were used to helpidentify which baseline values would be used forthe irradiated data to evaluate yield stresschange. This was complemented by a system tokeep track of the location in the billet fromwhich specimens were obtained, so that in highvariability cases, data from specimens fromsimilar regions could be used to evaluate yieldstress changes. Wafers comprised of theinterstitial pieces between tensile specimenpunch-outs were also included in some of theirradiations for the purpose of microhardnessand/or microstructural characterization. Smallangle neutron scattering (SANS) specimens1.135 cm x 1.2 cm x 2 mm were also machinedfrom selected materials and included in theirradiations.

3.2 Irradiations

Results for four irradiations, designated T4, T14,VSR, and PB are the primary focus of thisreport. The specimens and materials included inthese irradiations are listed in Tables 3-6through 3-8. The T4 and T14 capsulescontained tensile, wafer and SANS specimens ofall of the materials. The VSR capsule containedspecimens from the CM alloys subjected to the

7

Table 3-1. CM-Series Alloy Compositions and Heat Treatments

COMPOSITION (weight per cent)

Alloy Cu Ni Mn Cr Mo P N C Si S As/Sb Al B(ppm) ISn (ppm)

CMI 0.01 0.01 1.67 0.04 0.56 0.003 <50 0.13 0.15 0.004 0.005 0.025 <1CM2 0.01 0.01 1.65 0.04 0.56 0.041 <50 0.14 0.16 0.004 0.005 0.022 <1CM3 0.02 0.85 1.60 0.00 0.49 0.006 <50 0.13 0.16 0.000 0.005 0.002 <1CM4 0.02 0.86 1.53 0.05 055 0.031 <50 0.16 0.16 0.003 0.005 0.006 <1CMS 0.02 0.86 1.61 0.04 0.53 0.050 dO 0.15 0.16 0.000 0.005 0.005 <1CM6 0.02 1.68 1.50 0.05 0.54 0.007 <50 0.15 0.17 0.003 0.005 0.006 <1CM7 0.00 1.70 1.55 0.05 0.56 0.047 <50 0.16 0.17 0.003 0.005 0.003 <1CM8 0.01 0.86 0.01 0.04 0.55 0.004 <50 0.13 0.14 0.002 0.005 0.026 <1CM9 0.01 0.86 0.85 0.04 0.55 0.003 <50 0.15 0.15 0.003 0.005 0.013 <1CMIO 0.02 0.88 1.66 0.05 0.53 0.008 <50 0.16 0.17 0.004 0.005 0.003 <1CMI1 0.34 0.85 1.64 0.02 0.53 0.006 <50 0.15 0.18 0.003 0.005 0.003 <1CM12 0.86 0.84 1.65 0.02 0.51 0.006 <50 0.15 0.17 0.003 0.005 0.002 <1CM13 0.11 0.83 1.61 0.00 0.51 0.004 <50 0.15 0.16 0.000 0.005 0.002 <1CM14 0.11 0.83 1.62 0.00 0.52 0.040 <5O 0.16 0.17 0.000 0.005 0.003 <1CM15 0.22 0.02 1.59 0.02 058 0.002 <50 0.14 0.15 0.003 0.005 0.019 <1CM16 0.22 0.82 1.58 0.00 0.51 0.004 <50 0.16 0.25 0.000 0.005 0.003 <1CM17 0.22 1.59 1.54 0.00 0.50 0.004 <50 0.16 0.25 0.000 0.005 0.003 <1CMI8 OA3 0.02 1.70 0.02 0.56 0.002 <50 0.14 0.15 0.003 0.005 0.017 <1CM19 0.42 0.85 1.63 0.01 0.51 0.005 <50 0.16 0.16 0.003 0.005 0.003 <1CM20 0.43 1.69 1.63 0.02 0.50 0.006 <50 0.16 0.16 0.003 0.005 0.003 <1CM21 0.42 0.84 0.01 0.02 058 0.002 <50 0.14 0.14 0.003 0.005 0.015 <1CM22 0.42 0.84 0.84 0.02 0.56 0.002 <50 0.14 0.14 0.003 0.005 0.010 <1CM23 0.02 0.83 1.62 0.04 0.55 0.002 <50 0.03 0.15 0.003 0.005 0.015 <1CM24 0.02 0.87 1.65 0.05 0.52 0.010 <50 0.34 0.15 0.003 0.005 0.004 <1CM25 0.01 0.87 1.53 0.05 0.52 0.003 200 0.14 0.17 0.002 0.005 0.018 <1CM26 0.01 0.87 1.66 0.05 0.52 0.006 <50 0.16 0.17 0.003 0.020 0.003 <1CM27 0.02 0.84 1.60 0.05 0.51 0.002 <50 0.16 0.16 0.003 0.005 0.002 10CM28 0.42 0.84 1.60 0.02 0.51 0.002 <50 0.16 0.17 0.003 0.005 0.002 10

.CM29 0.21 0.02 1.68 0.02 0.02 0.002 <50 0.14 0.14 0.003 0.005 0.015 <1CM30 0.22 0.86 1.64 0.42 0.50 0.006 <50 0.16 0.16 0.003 0.005 0.003 <1CM31 0.01 0.80 1.65 0.05 0.51 0.006 <50 0.16 0.17 0.003 0.005 0.034 <1

8

Table 3-2. Stress Relief Anneal Matrix

Alloys: CM3, CM 5, CMI 1, CM12, CM13, CM16,CM18, CMI9, CM20

Slow Cool Matrix: Stress relieved at the followingtimes and temperatures followed by a program cool at8'C/h to 300'C followed by an air cool

Temperatures (C) Times (h)

590607624641as-tempered

24,48, 9612,24,48,9612,24,486,12,24

Variable Cool Matrix: Stress relieve at 607'C for 24h,air cool

Table 3-3. LV-Series Alloy Compositions and Heat Treatments

Composition (weight percent)tt

Code C Cu Ni Mn Si

LA 0.14 0.40 0.00 1.37 0.22LB 0.14 0.40 0.18 1.35 0.22LC 0.14 0.41 0.86 1.44 0.23LD 0.19 0.38 1.25 1.38 0.23LG 0.16 0.00 0.74 1.37 0.22LH 0.16 0.11 0.74 1.39 0.24LI 0.16 0.20 0.74 1.37 0.24Li 0.16 OA2 0.81 1.34 0.13L( 0.13 0.80 0.81 1.13 0.13LO 0.14 0.41 0.86 1.44 0.23

tt Alloys contained P <0.005, S 5 0.015, Cr 5 0.085, Mo - 0.55; they were austenitized900°C/lh; air cooled; tempered 664°C/4h; air cooled; stress relieved 600°C/40h; furnacecooled to 300°C; air cooled. With the exception of LO, which was not stress relieved aftertempering

9

Table 3-4. Commercial Steels

COMPOSITION (weight per cent)

Code C Mn P S Si Cr Ni Mo Cu V HT*

A 0.08 1.69 0.014 0.013 0.45 0.14 0.63 0.40 0.21 - IB 0.09 1.63 0.018 0.009 0.54 0.10 0.69 0.40 0.28 - 2C 0.08 1.30 0.009 0.010 0.37 0.08 0.62 0.31 0.06 -- 362W 0.08 1.61 0.020 0.007 0.59 0.12 0.60 0.39 0.23 0.01 463W 0.10 1.65 0.016 0.011 0.63 0.10 0.69 0.43 0.30 0.01 565W 0.08 1.45 0.015 0.015 0.48 0.09 0.60 0.39 0.22 0.006 667W 0.08 1.44 0.011 0.012 0.50 0.09 0.69 0.39 0.27 0.007 773W 0.10 1.56 0.005 0.005 0.45 0.25 0.60 0.58 0.31 - 8Midland 0.08 1.61 0.017 0.007 0.62 0.10 0.57 0.41 0.27 0.004 9EPRI C 0.16 1.55 0.005 0.009 0.17 0.04 0.60 0.44 0.35 10A302B 0.21 1.20 0.015 0.017 0.28 0.24 0.20 0.60 0.14 0.004 11HSST02 0.23 1.55 0.009 0.014 0.20 0.04 0.67 0.53 0.14 0.003 12JRQ 0.18 1.40 0.019 0.004 0.25 0.12 0.82 0.50 0.14 0.003 13

*Heat Treatments1. Post weld heat treatment (PWHT) 607'C for 15 h, furnace cool2. PWHT, 607'C for 23 h, furnace cool3. PWHT, 607C for 13.5 h, furnace cool4. Submerged arc wild (SAW): stress relieved (SR) 8 cycles of 6 h at 593-621 C5. SAW, SR 48 h at 593-621 C6. SAW, SR 80 h at 593-621 C7. Not available8. PWHT 607'C, 40h9. PWHT 607*C, 22.5h10. SAW, PWHT 620C, 50h11. Normalized and tempered; tempered for 6.5 h at each of 926-C, 885-C, 648'C, and 607-C, WQ12. Austenitized 871 C, water quench; tempered 663C, 4 h; FC; stress relieved 607C, 40h, FC13. Normalized @ 900T, quenched at 880-C, tempered at 665C for 12 h, SR at 620C 40h

10

Table 3-5 VM-Series Alloy Compositions

Composition (Weight per cent)*Alloy Cu Mn N C Ti

(appm)

VA 0.000 0.00 5 0.00 0.000VB 0.020 1.01 40 0.01 0.002VC 0.020 1.03 30 0.17 0.004VD 0.875 1.03 10 0.00 0.000VE 0.910 1.08 20 0.16 0.010VG 0.510 0.06 20 0.01 0.002VH 0.910 0.01 20 0.01 0.010VI 0.510 0.05 10 0.17 0.003VJ 0.890 0.02 10 0.17 0.005VK 0.020 0.02 100 0.01 0.001VL 0.010 0.01 100 0.00 0.300VM 0.510 0.01 120 0.01 0.010VN 0.875 0.00 110 0.00 0.000VO 0.910 0.00 110 0.16 0.000VP 0.900 0.01 110 0.00 0.300VR 0.010 1.06 100 0.01 0.010VS 0.920 1.00 110 0.00 0.002VT 0.880 1.00 90 0.00 0.260

*Solution treat 775C, 17h; quench in salt bath at 450*C, 3 minutes, air cool

11

variable stress relief series described above.The PB capsule contained specimens for theLV-series and CM-series. As describedpreviously, for this irradiation the CM alloyswere primarily in the as-tempered condition;however, selected alloys were also irradiated inseveral alternative heat treatment conditions.

For the T4, T14 and VSR irradiations,specimens were loaded into aluminum boxes2.54cm x 2.54cm x lcm deep. Once loaded,the specimens were shimmed with aluminumfoil, and an aluminum cover plate was screwedon. These capsules were machined to finaltolerance and shipped to the University ofMichigan for irradiation in the IVAR(Irradiation VARiables) facility.

IVAR was collaboratively designed by UCSBand ORNL, and it was fabricated and isoperated by ORNL. It consists of a sealedcontainer incorporating 50 electrical heatersand has 49 thermocouples to monitortemperatures. The entire facility is enclosed ina boral shield to reduce activation fromthermal neutrons. Two removable specimenbaskets contain the irradiation capsulesdescribed above. The facility has two separatesections referred to as the high flux (HF) andthe intermediate flux/low flux (IFILF) sections.The HF portion of the facility consists of aremovable specimen basket, which can contain2 capsules at each of 2 different temperatures(nominally 270 and 310'C) and 14 capsules ata third temperature (nominally 290'C). TheIF/LF section consists of a removable basketwhich can contain 9 capsules and one halfcapsule at each of 2 different temperatures(nominally 270 and 310'C) and 18 capsulesand 2 half capsules at a third temperature(nominally 2900C). The specimen basketswith their sliding cover plate are shown inFigure 3-1 and a schematic diagram of theirradiation facility is shown in Figure 3-2.

The Ford Nuclear Reactor (FNR) is a 2 MWpool-type reactor located on the campus of theUniversity of Michigan in Ann Arbor,Michigan. The reactor nominally operates on

a fixed cycle consisting of 10 days ofoperation at full power, followed by a 4-daymaintenance shutdown. Experimentalfacilities are located in a grid assembly locatedon the south and east faces of the reactor. TheIVAR facility, and two companion ORNLfacilities, are located on a movable carriage atthe southeast corner of the reactor. The fullyloaded IVAR facility, including dummyblocks, is brought to temperature in a retractedposition. The facility is then moved up againstthe reactor face at full power. The HF zonesits closest to and the LF zone furthest fromthe reactor face. At the end of an irradiationcycle, the facility is moved to the retractedposition, away from the reactor face. When acapsule(s) reaches its target fluence, the basketcontaining it is loaded into a shielded transfercask. The HF and IF/LF baskets can beremoved independently. The basket(s) istransferred to a hot cell in the transfer caskwhere the capsule(s) is removed and replaced.The basket(s) is then returned to the IVARfacility using the transfer cask. Hence, thedesired irradiation temperature, flux andfluence is achieved by locating a capsule at theappropriate site in the facility and exposing itfor the requisite time. Estimated uncertaintiesin the irradiation temperature are 5'C.

Prior to its installation, the flux in the IVARlocation was mapped by a multiple foilactivation experiment [Remec, 19981. Duringthe first cycle of IVAR operation 16 additionalsets of Fe and Ni wires and 7 multiple foil setswere located throughout the IVAR baskets andsubsequently removed and counted after thefirst cycle. The fluxes reported [Remec, 1997]were in reasonable agreement with the initialmap, although there appeared to be a slightreduction in the higb flux positions. Inaddition, every capsule that has been irradiatedin IVAR has included an Fe and Ni wire pair.Nine of these have been counted from 6locations. The activity measurements werecarried out by J. Adams of the NeutronInteractions and Dosimetry Group at NIST inGaithersburg, MD. Analysis of these data

12

IF/LF Basket

-SpecimenPackets

Figure 3-1 Specimen Baskets in the IVAR Facility

13

'HF Basket

Cover

,Top Plug

1My/Instrumentation"on

Singl-WallContainment

-Transition29Zo

Double-WallContainment

High-Flux (HF)- Region

DOC.no

310C,Zone

2700CZone

Intermediate-Flux (F) I -Low-Ftux LF) Region

"o ;20 n.

0.5 In,Hall Subcapsule

(4 Used)

MountingBlock

Covers Removed toShow Subcapsules

iadiation Facility

Figure 3-2 Schematic Design of the IVAR Irradiation Facility

14

Table 3-6. Specimen Loadings for Capsules T4 and T14

material T4 T14

tensile SANS wafer tensile SANS

ORNL Midland WeldORNL 73 WeldORNL A302bORNL HSST02 plateB.W. A508 plateB.W. A weldB.W. B weldB.W. C weldB.W. 62 weldB.W. 63 weldB.W. 65 weldB.W. 67 weldRolls Royce WVRolls Royce WGRolls Royce WPEPRI C weldJRQCMICM2CM3CM4CM5CM6CM7CM8CM9CMIOCMIICM12CM13CM14CM15CM16CM17CMiCM19CM2oCM21CM22CM23CM24CM25CM26CM27CM2SCM29CM30CM31LALBLCLDLGLHULlLKLO

3 23 13 2

I

3 13 13 13 1

3 23 1

3333333333333333

4 1 1

4 14 1

3

34344444

3333333333

15

II

III

II

I

Table 3-7. Capsule loading for VSR

Stress Relief time - - Alloy - - - -

And temperature CM3 CM5 CMII CM12 CM13 CM16 CM18 CM19 CM20590'C 24h 2t* 2t 2t, Is 2t 2t 2t 2t 2t 2t

1w 1w Iw 1w 1w 1w 1w 1w 1w

590C 48h 2t 2t 2t 2t 2t 2t 2t 2t 2t

5900C 96h 2t 2t 2t 2t 2t 2t 2t 2t, Is 2t

1w Iw 1w 1w Iw 1w Iw 1w 1w

607'C 12h 2t 2t 2t 2t 2t 2t 2t 2t, Is 2t

Iw Iw Iw Iw Iw Iw Iw Iw Iw

6070C 24h 2t 2t 2t, Is 2t 2t 2t 2t, Is 2t, Is 2t, Is

607C 48h 2t 2t 2t 2t 2t 2t 2t 2t 2t

607'C 96h 2t 2t 2t, Is 2t 2t 2t 2t 2t, Is 2t

1w 1w 1w 1w 1w 1w 1w 1w 1w

624 C 12h 2t 2t 2t 2t 2t 2t 2t 2t 2t

624 C 24h 2t 2t 2t, Is 2t 2t 2t 2t 2t, Is 2t

624 C 48h 2t 2t 2t 2t 2t 2t 2t 2t 2t

1w 1w lw Iw 1w 1w 1w 1w 1w

641'C 6h 2t 2t 2t 2t 2t 2t 2t 2t 2t1w 1w 1w 1w 1w 1w 1w 1w lw

641 C 12h 2t 2t 2t 2t 2t 2t 2t 2t, Is 2t

641 C 24h 2t 2t 2t, Is 2t 2t 2t 2t 2t 2t1w 1w 1w 1w 1w 1w 1w 1w 1w

As-tempered 2t 2t 2t, Is 2t 2t 2t 2t 2t, Is 2t

1w 1w 1w 1w 1w 1w 1w 1w 1w

607;C 24h, air 2t 2t 2 21 2t 21 2t 2t, s 2tcool

* t = tensile, w= wafer, s=SANS specimen

16

Table 3-8. Capsule loading for PB

Material

CMI as temperedCM2 as temperedCM3 as temperedCM4 as temperedCM5 as temperedCM6 as temperedCM7 as temperedCMS as temperedCM9 as temperedCMIO as temperedCMII as temperedCM12 as temperedCM13 as temperedCM14 as temperdCMI5 as temperedCM16 as temperedCM17 as temperedCMI8 as temperedCMI9 as temperedCM20 as temperedCM21 as teperedCM22 as temperedCM23 as temperedCM24 as temperedCM25 as temperedCM26 as temperedCM27 as temperedCM28 as temperedCM29 as temperedCM30 as temperedCM31 as temperedCM5 aged 480-C 10hCM8 salt quenched 400CCM12 SR 600C 8hCMI8 SR 600C 40hCM19SR600CShCM19 SR600C40hCM19SR600C80hCM19 salt quenched 500CCM20 SR 600'C 40CM20 it quenched 500CCM23 st quenched 400-CCM26 aged 480C OOhLALBLCLDLaLHLiuLK

tensile

2223322332222222231133322222222222222222222222

222222

SANS wafer

2 338

2 52 52 3

33333

2 32 3

33

2 32

2 32 112 32 32 3

33333333333

2 32 32 32 32 3

32 3

333

1 22

11 21 21 21 21 21 2

17

using cross sections from the preliminary ORNLreport indicated good agreement with theprevious estimate of flux levels. More recently,ORNL remapped the flux distribution in andaround the IVAR facility based on new crosssections and neutron transport calculations. Theestimated flux levels were generally slightlylower, but in most cases only by a few percent.However, several locations showed fluxreductions as large as 7%. The fluence estimatespresented in this report (in units of 10'3 n/M2 E >I MeV) are based upon the most updated fluxlevels at each position in the IVAR facility. Thefluence estimates for the T4, T14, and VSRcapsules are shown in Table 3-9. Final fluenceswill be based on any further updates of theactivation cross sections and activitymeasurements on the dosimetry wires fromindividual capsules.

In the case of the PB irradiation, specimens wereloaded into a pair of aluminum sub-capsulesspecifically designed to fill the space betweenthe clevis tabs in a row of large crack arrestspecimens. These specimens were included in alarge instrumented irradiation capsule built byORNL as part of the HSSI program. Thiscapsule was irradiated at FNR during the latterpart of 1993. Temperature was measured byinternal thermocouples and dosimetry wasperformed by ORNL [Remec, 1998]. Theirradiation conditions for the PB irradiation arealso given in Table 3-9.

3.3 Tensile Testing

Following irradiation, the IVAR capsules werereturned to UCSB where specimens wereremoved, sorted and cleaned to remove anyminor surface contamination . Followingcareful measurements of the gauge dimensionsto about ± 5pm, the tensile specimens wereloaded into a linear carriage for automatedtesting. The automated tensile tester consists ofa screw driven load frame, a linear drive, apneumatically actuated hydraulic upper grip anda computer control and data logging system.The linear carriage holds 29 tensile specimensand serves as the lower grip. It mounts on the

linear drive. During a testing sequence, the driveprecisely locates a specimen under the uppergrip. The upper grip closes, and motion of theis crosshead initiated. Loads are measured witha precision calibrated load cell aligned with theupper grip. Displacements between the bottomof the upper grip and the lower carriage aremeasured by an LVDT. The load-displacementsignals are digitized and continuously recordedand monitored on a desktop computer during atest. The crosshead is stopped when the load hasdecreased 10% below it's maximum value. Theupper grips are opened and another specimen ispositioned for the next test. Yield strength,ultimate tensile strength, and uniform elongationare immediately calculated from the load-displacement data and specimen dimensions, andloaded into a data base. However, each testrecord is also examined to verify the resultsgenerated by the computer. Three calibratedstandard specimens are included in everycarriage to ensure data reproducibility.

A minimum of two tensile tests were conductedfor each irradiation and unirradiated controlcondition. Additional tests were typically cariedout on unirradiated specimens, as well as theirradiated specimens in a number of cases. Yieldstress changes (o,) were determined bysubtracting the average unirradiated (baseline)from the average irradiated yield stress. Asnoted previously, both microhardnessmeasurements and billet location tracking wereused to reduce scatter in Aa, due to variability inthe baseline properties. This included bothmatching irradiated and control specimens andscreening the data for cases where the accuracyof Aa was in some question. In a very few casesthis reduced the number of test points below thenornal minimum of two.

The estimated uncertainties in individual cy,values were based on the root of the sum of thesquares of the standard errors (or the ay rangein the case of only two tests) of the unirradiatedand irradiated data. The estimated uncertaintiesin Ac, averaged about ±11 MPa, but wheresignificantly higher in some cases. The largestuncertainties were experienced in the VSR study.

18

Table 3-9. Irradiation Conditions

Capsule Irradiation Conditions

Flux Fluence Temperature

(10 r nLrm-s) (10 n/rn) (C)

T4 0.97 0.75 290

T14 0.32 0.48 290

VSR 0.97 0.85 290

PB 0.7 1.0 288

This led to a data screening procedure, describedin Section 6. 1, for the A5, used to estimatematrix copper levels.

3A Small Angle Neutron Scattering

The Small Angle Neutron Scattering (SANS)measurements were performed at the NationalInstitute of Standards and Technology (NIST).Details of the experiments and data analysis arepresent elsewhere [Mader, 1995; Wirth, 1998].The approach can be briefly sunmarized asfollows. All measurements were made in astrong (1.8±0.IT) magnetic field oriented in the* = 0 horizontal direction. The scattering atsmall angles, e : 8°, from a well collimated beamof cold neutrons with a wavelength of - 0.5nm, was measured on a 64x64 cm positionsensitive detector located about 2 meters fromthe sample and rotated off the beam axis by 5°to increase the scattering vector. The detectorrecords the number of scattered neutronsdetected in each 0.5xO.5 cm pixel element. Theirradiation-induced feature scattering cross-

sections are obtained by subtracting off thecorresponding, properly normalized(measurement time, sample volume andattenuation) counts from: a) backgroundradiation; b) parasitic scattering not associatedwith the sample itself; and c) scattering from anunirradiated control. The corrected defectscattering data are then converted to an absolutedifferential defect scattering cross-sectiond3IdCl(q, ) by a normalization tocorresponding measurements on a waterreference sample with a 'known' isotropicscattering cross section. ( 0.88 /cm-ster) [Wirth,19981.

The differential coherent small angle crosssection, £/dQ for a dilute distribution of singletype scattering feature is given by [Kostorz;Guinier and Foumet, 1955]

d.VdQ(q,) = NV 2 Ap2 F(qr) (3-1)

where:

19

a) N, r and V are the number density,characteristic size (e.g., radius) and volume ofthe feature, respectively. b) F is the scatteringfunction which depends on feature size (r) andshape, and the scattering vector, q = Usin(9)/X,where O is half the scattering angle (26), and isthe neutron wavelength; for spherical features,

F(qr) = 31 [sin(qr) - qrcos(qr)y(qr) 3)2 (3-2)

c) Ap is the difference (or contrast) between thescattering length density of the feature (f) andthe matrix (m) or (Ap = pf Pm); here p is thescattering length density defined as p = blwhere b is the average scattering length (nuclearor magnetic in the feature or matrix) and isthe corresponding average atomic volume.Coherent small angle scattering is produced byboth nuclear APN and magnetic APM contrast,and the total scattering contrast (p 2) is givenby

Ap2 = APN2 + ApM2 sin2 (%s) (3-3)

where ¢, is the angle with respect to the appliedmagnetic field.

As noted above, the dlYd[(q,,) data includecontributions from both nuclear (N) andmagnetic scattering (M), thus

d/d(qks)=dcdn N(q) +dJdflm(q) sin2 ) (3-4)

The d£1dS2 increases from purely nuclearscattering at O' = 00 to nuclear plus magneticscattering at +, = 900. The dVdl data at eachdetector pixel were averaged over a set ofspecified magnetic angle sectors, 0i+,, for a setof discrete q,Aq . The corresponding standarddeviations were calculated for each averageddefect cross section.

The nuclear scattering, Ap2. depends on thefeature composition. It is assumed that thefeatures are magnetic holes in a saturatedferromagnetic iron matrix; hence, that themagnetic scattering, AP 2, is independent ofcomposition [Fint, 1990; Mader, 1995; Wirth,

1998]. This is useful in two ways. First, themagnetic to nuclear scattering ratio (MIN)provides information about the composition ofthe scattering feature (see below). Second, goodabsolute estimates of the number density andvolume fraction of the scattering features can beobtained from dl:(qydg, since APM2 is preciselyknown. Single, and in some cases multiple,feature fits are made to the dX/dIWq,O) databased on the M/N ratio determined from dl,VdQvs. <sin2()> fits typically over a q-range whereirradiation-induced feature scattering isdominant.

The d£/dQ data was analyzed assuming the sizedistribution of the features can be approximatelydescribed by a log-normal distributioncharacterized by a mode radius r, and radiusdistribution parameter, P. Non-linear leastsquares fits to the data were carried out todetermine r,, P and dZ/dQ,(o = 0). These fitparameters can be related to the average of theradius cubed (<r?>P3 = <r>), number density (N)and volume fraction (f) of the features as [int,1990; Mader, 1995; Wirth, 1998]

r> = r,.exp(O.75f 2 ) (3-Sa)

N = (3/4x) 2fexp(-9VY[rm6Ap2] dJdtam(O)(3-5b)

fv = (314x){exp(-6.75yrm3Ap2]) dYIdClM(O)(3-5c)

Note the 3 and r. parameters have a largecovariance coefficient, hence, cannot beindependently determined with good precision.This has relatively little effect on the estimates ofa> and f, but results in larger uncertainties in N.A fixed 0 of 0.4 was used for most single defectfits to provide a more self-consistent basis toassess trends in <r>, f and, particularly, N.

As noted previously the M/N ratio providesinformation on the composition of the scatteringfeature. It is useful to characterize the relativestrengths of nuclear and magnetic scattering as R= 4N/M (= Ap/APN), rather than MIN, since it isapproximately a simple linear function of the

20

composition, R = CcXc. + C.A. where the C'sare known coefficients and X's are the atomfractions [Mader, 1995; Wirth, 1998]. Forexample, the nominal R for a spherical void anda pure copper precipitate in an iron matrix areabout 1.58 and 0.36, respectively [Wirth, 1998].If the copper-rich precipitates (CRPs) containmore than two elements (e.g. Cu, Mn and Ni),the R is not a unique quantity. However, Rconstrains and can be used along with otherinformation to estimate CRP composition. Theother information includes: a) the CRP volumefraction; b) the amount of copper (and otherelements) in the CRPs based on independentmeasurements of changes in the matrix levels; c)use of isotopically modified constituents; d) datafrom atom probe and other microanalyticaltechniques such as positron annihilationspectroscopy; e) thermodynamic calculations;and f) hardening measurements [Wirth 1998].

3.5 Field Emission Gun ScanningTransmission Electron Microscopy

Field Emission Gun Scanning TransmissionElectron Microscopy (FEGSTEM) wasperformed on a number of alloys in theunirradiated condition to evaluate the amount ofcopper in solution as a function of heattreatment. The FEGSTEM studies wereperformed at AEA Technology in acollaborative program with UCSB. Standard0.5x3mm transmission electron microscopy(TEM) specimens were examined in a VGHB501 STEM and a Philips EM430conventional TEM. The STEM is fitted with aparallel electron energy loss spectrometer(PEELS) and an energy-dispersive X-ray (EDX)detector. The relative concentration of copperinteracting with the electron beam is determinedfrom the ratio of the counts under the copperpeak to the counts under the peak of a referenceelement, typically taken as iron [Kenway-Jackson, 1993].

The measurement of matrix copper with theSTEM EDX was determined as follows[Kenway-Jackson, 19931. The foil preciselypositioned in the STEM in a specially-modified

holder of copper-free construction. X-rayspectra were recorded from regions free of anyvisible precipitates using the so-called spot modeor small area mode, where the small areas werefitted between dislocations. Precipitates withdiameters larger than about Snm were alsogenerally avoided by the small areameasurements. The small area measurements inthe STEM determine the average copper contentbetween dislocations and large precipitates, whilethe spot analyses measure the copper contentbetween dislocations and all visible precipitates.The visibility limit of the HB501 STEM is aprecipitate diameter of around 2nm. Therelationship of these two types of measurementto the bulk copper content and to each other,and the variation within a series of measurementsof a given type, changes with the type and extentof precipitation, as explained below:

1. When no precipitation has occurred and thedissolved copper is evenly distributed, bothspot and small area measurements are thesame as the bulk measurement and thedistribution about the mean will be relativelynarrow.

2. When heterogeneous precipitation occurs ondislocations and grain boundaries, then thesmall area and spot measurements will againbe tightly distributed about a mean, but themean will be less than the bulk copper level.The difference between the bulk and themean represents the amount of copperbeterogeneously precipitated.

3. When some homogeneous matrixprecipitation occurs and the precipitates areextremely fine (diameter, d < 2nm), theprecipitates are not easily visible in the STEMimages and are included in both the spot andthe small area measurements. In this case thesmall area measurements overestimate thedissolved copper content. Since the spotmeasurements, randomly sample both matrixand precipitates, the average spotmeasurement will be equal to the averagesmall area measurement. However, thedistribution of individual spot measurements

21

becomes skewed and/or broadened, and thelower end of the distribution correspondsmore closely to the true matrix level ofcopper.

4. When homogeneous precipitation hasoccurred and the precipitates have grown tomore than 2nm, the precipitates are visible inthe STEM images and can be avoided duringspot analysis. Under these conditions, thespot measurement distribution will onceagain become tight about a mean thatrepresents the best estimate of the matrixcopper level.

5. When further growth of matrix precipitatesresults in diameters well over Snm, theprecipitates can be avoided by the small areameasurements as well as the spotmeasurements; and the spot and small areameasurements will again be equivalent. Theirmeans will provide a best estimate of thematrix solute content. The differencebetween the bulk and small areameasurements will then include acontribution from the large matrixprecipitates as well as the precipitates ondislocations and grain boundaries.

Hence, the differences between bulk (or largearea), small area, and spot measurements as wellas the distribution of spot and small areameasurements provide a method of estimatingboth the copper in solution as well as the sizeand spatial distribution of copper precipitates.When both heterogeneous and homogeneousprecipitation occur concurrently (the mosttypical situation), the bulk measurement will begreater than the STEM small area measurement,and the STEM small area measurement will begreater than the spot measurement. Thedifference between the bulk and STEM smallarea measurements will then show the extent ofheterogeneous precipitation, the differencebetween the STEM small area and spotmeasurements indicates the extent ofhomogeneous precipitation producingprecipitates with diameters greater than 2nm.The distribution of the spot measurements will

give information on the precipitates of diameterless than 2nm. Once again, in this case the bestestimate of the dissolved copper level is given bythe spot measurements. Depending on thesituation, the best estimate of copper in solutionin the presence of small precipitates can beobtained by either the mean of the lower peak ina spot distribution or the mean of the lowest fourmeasurements. Summarizing, the amounts ofcopper tied up in the various precipitate sizecategories can be taken as:

1. The dislocation precipitate content is the bulkcopper level minus the mean of the smallarea

2. The homogeneous precipitate content(diameters above 2nm) is the mean small arealevel minus the mean spot level

3. The homogeneous precipitate content(diameters below 2nm) is the mean spot levelminus the matrix level

4. The matrix copper level taken as the mean ofthe four lowest spot measurements, or themean of lowest peak in spot distributionwhere relevant.

These working rules to establish the matrixcopper level from FEGSTEM data weredeveloped based on extensive Monte Carlostudies of STEM electron beam interactions witha range of precipitate structures. However, theoverall accuracy is limited and in general is oforder ±0.05% copper. The limitations of eventhese highly sophisticated measurements andanalysis methods demonstrate the challenges toprecisely characterizing the effects of pre-precipitation during stress relief on matrixcopper levels.

3.6 Electrical ResistivityMeasurements

Electrical resistivity (expressed in pil-cm in thisstudy) is a function of the solute content of thematrix, and it can be precisely measured[Rossiter, 1991; ASTM, 1987]. Tests were

22

performed on tensile specimens used in theirradiation experiments. The width andthickness of the guage section of the specimenswere carefully measured to 51pm. The specimenwas mounted and aligned on a Teflon supportblock containing two copper electrodes thatcontacted the tab ends of the specimen. Theseelectrodes were attached to a DC constantcurrent power supply. An upper blockcontaining two copper knife edge electrodes waslowered onto the specimen, guided by alignmentpins. The knife edges were located at a preciselyknown distance apart along the specimen gaugesection. They were loaded on the specimen witha fixed weight. A current was applied andmeasured with a precision ammeter. Thecorresponding voltage drop across the knifeedge electrodes was measured with a highprecision DC nanovoltmeter. The current andvoltage was read by a desktop computer, andalong with the specimen dimensions and knifeedge spacing were used to compute theresistivity. The entire apparatus was maintainedin an electrically and thermally insulatedcontainer The sample temperature wasmeasured with a thermocouple attached to thesupport block adjacent to the specimen. Testswere performed at ambient temperature, in therange of about 20-25-C. In this range, theresistivity was linear with temperature with acoefficient of about 0.08 tfl-ciC. Theresistivities was normalized to a referencetemperature of 23°C for data intercomparisons.Resistivities of the alloys examined in this studyranged from about 10-27 p5cm. Typicaluncertainties were on the order of ±0.05 pfl2cmfor a single specimen, and up to about 0.5 I.0-

cm between specimens of the same material. Theaverage uncertainty was about ±0.2 pf-cm.

3.7 Seebeck CoefficientMeasurements

Similar to resistivity, the Seebeck coefficient of ametal or alloys is very sensitive to theconcentration of dissolved solutes [Pollock,1991; Miloudi et. al, 1999, 2000]. The Seebeckeffect relates to the electric potential differenceestablished between junctions of dissimilar

conductors in a temperature gradient.Thermoelectric power derives from threeinterrelated effects: the Peltier effect, theThomson effect, and the Seebeck effect. Theseform the basis for both thermocouples andthermoelectric power generators [Pollock,1991]. As noted above, the Seebeck effectoccurs when dissimilar conductors in contactform a circuit that produces an electric potentialwhen the two junctions are held at differenttemperatures. The Seebeck coefficient, S (inunits of pV 0K) is the open circuit potentialdivided by the temperature difference.

The Seebeck coefficient is determined bymeasuring the potential difference of an opencircuit composed of a pure copper referencematerial and the samples, typically in the formof tensile specimens. Thus the potential is forthe sample relative to copper and is not anabsolute value. The absolute value is found bycorrecting for the absolute potential of thereference material, in this case copper. Thesample was aligned in a fixture and held againstthe copper electrodes with a fixed weight. Oneof the electrodes was at ambient temperaturewhile the other was heated with a resistance tapeto about 100 higher. The temperatures in theknife edges just below the sample were measuredwith thermocouples to within ±0.1°C. Thepotential difference was measured with aprecision nanovoltmeterto within :tl.5pV. Carewas taken to avoid noise or spurious electronicsignals, and copper leads of equal length wereused to minimize any extra potential notassociated with the specimen itself. Theinstrument was calibrated with copper andaluminum reference materials with knownabsolute values of S. A nominal temperaturecoefficient for S of 0.022 pVrK' was used tocorrect the data to a nominal average sampletemperature of 31°C. Typical uncertainties werej0.05 pVrK for a single specimen, and up toabout O.5 pVrK between specimens of thesame material. The average uncertainty is about±0.25pV/K

23

4 EFFECTS OF COMPOSITION ON IR*ADIATIONHARDENING AND EMBRITTLEMENT

The empirical trends of A;Y variations with alloycomposition are described in this section. Thedata are derived from the T4, T14, VSR and PBcapsules. Except for the PB capsule, whichcontained specimens in the as-tempered heattreatment condition, or as otherwise noted, all thealloys are in a tempered plus standard stressrelief condition. The heat treatment schedulesare described in Section 3.

4.1 Summary of the Data Trends

4.1.1 Copper Bearing Alloys

Figure 41 plots the A;, of the intermediatenickel (0.74 to 0.88%) CM and LV alloys versusbulk copper content (Cub,). The data are fromthe T4, T14 and VSR capsules. Figure 4-lapresents results for the CM-series (CM3, 10,11,12, 13,16 and 19) and 4-lb for the LV-series(LG, LH, LI, LC, LJ, LK), respectively. In bothcases Aa, (Cub,) has a typical sigmoidal shape,with a low copper threshold region and a highcopper saturation, followed by a decrease at veryhigh copper levels. In between Au. increasesrapidly with increasing Cu,,.

Figure 4-2 shows the corresponding effects ofnickel variations on A(oY for intermediate andhigh copper steels. The data are from the T14and PB capsules. Figure 4-2a shows data for thehigh copper (0.43%) CM-series (CM 18, 19, 20).In all three cases, A; increases approximatelylinearly with nickel, as Aa,(Ni) = A + BNi. Theaverage zero-nickel intercept is A = 63 6 MPaand the average slope is B = 117±8 MPal%Ni.Figure 4-2b shows a similar plot for theintermediate copper (0.22%) CM alloys(CM15,16,17). In this case, the data for the as-tempered heat treatment condition from the PBcapsule is included, since pre-precipitation is notexpected to occur at these bulk copper levels(see Section 6). The Ay,(Ni) intercept is A =45±3 MPa and the slope B = 106±:10 MPaf%Ni.Figure 4-2c compares the Ay,(Ni) data forintermediate and high copper steels from the

T14 capsule. Notably, nearly doubling Cubk,results in only relatively small increases in theAur from about 18 MPa at low (0.0%) nickel to32 MPa at the high (1.7%) nickel. Figure 4-2dplots Aay, versus nickel for the high copper(0.40%) LV series. The corresponding data forthe high copper CM-series is shown as smallfilled symbols. The AG,(Ni) is very similar forthe CM and LV steels, with the exception of theLV data from the T4 capsule, which falls wellbelow the other data trends. The LV steels alsohave a slightly higher average intercept of A =71.8 5 MPa than the CM alloys (A = 63 MPafor the CM alloys), and a lower nickel sensitivitywith an average slope of B = 101± 15 MPaJ%Ni(B = 117 MPal%Ni for the CM alloys).However, in spite of these modest differences,overall the behavior of Ao,(Ni) for the LV andCM alloys are very similar. These results clearlyshow that for intermediate-to-high copper steels,nickel is the dominant compositional factorcontrolling embrittlement.

Figure 4-3 plots Ay, versus manganese content(0.0 to 1.65%) for the internediate nickel(0.85%), high copper (0.42%) CM alloys(CM19,21,22), as well as the LV steel (l) fromthe T4 and T14 capsules. The AG,(Mn) isapproximately linear, AG,(Mn) = A + BMn, withan average slope of B = 31±5 MPa/%Mn. TheAG, for the CM21 alloy with intermediatemanganese (0.84%) falls somewhat above thelinear trend line in both cases. Hence a AG,(Mn)= A + BMn + CMn2 type dependence mayactually be more appropriate. The effect ofmanganese is larger for the intermediate flux,lower fluence T14 irradiation compared to thehigh flux T4 capsule. This difference isconsistent with enhancement of a flux effect bymanganese (and nickel) that is discussed inAppendix A.

Figure 4-4 plots A, from the a) PB and b) T14capsules for other compositional variations inintermediate and high copper CM alloys,including: i) a 10 wt.ppm boron addition to the

24

cl

200

150

100

50

00 0.25 0.5 0.75

Cu (wt. %)

200

150

eS

1,

100

504

00 0.2 0.4 0.6

Cu ( %)

1

0.8 1

Figure 4-1 Variation of Acy with bulk copper in intermediate nickel alloys for thea) CM and b) LV series

25

I I

a CM-0.8%Ni* t

4 s

0 * T14

A A T4* * VSR& I -. I

* I U I

LV-0.8%Ni b

** A

a A

T14A * PBC

A T4

. y y y

. . .

r r | . r

Ia

CM - 0.4% Cu a

* T14

a T4

* VSR

0.5 1 1.5 2

Ni (wL %)

a IC x

CM - OA% Cu, T14 *

CM -0.2% u,TI

t CM - 0.2% CU, T4I

.-- -- -L- - - - -J

0 0.5

300

250

9

200

150

100

50

0

300

250

200

150

100

50

01 1.5 2

b X

CM - 0.4% Cu, T14 $

x0 T14

) T4

CM - 0.2% Cu * PBI ia, . i VSR

0 0.5 1 13 2

Ni (wt. %)

. ,

0.4% Cu CM (filled), * dLV unfilled)

0

d . @ * T14X t .~~ T4

* VSR

0 0.5

Ni (Wt. %)

1 1.5 2

Ni (wL %)

Figure 4-2 Variation of Acriwith nickel for a) 0.4 copper and b) 0.2 copper CM alloys;c) comparison of Aay versus nickel for intermediate and high copper steels for T14;

d) variation of Acty with nickel for high copper LV series steels(corresponding CM alloys shown for comparison as small filled symbols).

26

300

250

200

150

100

50

0

300

250

200

150

100

50

0

225

200

175

150

1254

1000 0.5 1 1.5

Mn (wt. %)

Figure 4-3 Variation of ac,y with manganese for intermediate nickel,high copper CM and LV steels.

250

200

-3 150

10

50

a

250

200

I9150

100

50

n

e w h o ,e an c m o ) 1

Figure 4-4 Variation of Acry with boron, molybdenum and chromium for a) PB and b) T14.

27

I . I a

0.4 Cu CM, LV

& LV

A CM

0O

0 &

I I I

2

b

T14

n 1. , . . |-

I

high copper (0.42%) and intermediate nickel(0.84%) alloy (CM27); ii) an intermediatecopper (0.22%) low nickel (0.02%) alloy(CM29) with no molybdenum (0.02% versus anominal value of 0.5%); and iii) an intermediatecopper (0.22%) and nickel (0.85%) alloy(CM30) with a 0.42% chromium addition. TheAa, for the modified alloys are compared to thecorresponding base steels (CM27 vs. CM19,CM29 vs. CM15 and CM30 vs. CM 16). Thealloys in the PB and T14 capsule are in the as-tempered and standard stress relief conditionsrespectively. The boron and chromiumadditions have a small to negligible effect.However, the Aa, in steels without molybdenumis larger in both cases.

While the overall effect of deledng molybdenumis modest (a difference of about 30±6 MPa), thistrend is consistent with a lower dispersedobstacle contribution to the unirradiated yieldstrength in this alloy, that lacks fine scale Mo2Ccarbides. As discussed in Section 6, thisbehavior arises from the fact that the individualstrengthening contributions from theunirradiated (aj and irradiation induced (a,)dispersed dislocation obstacles must becombined or superposed. For strongunirradiated obstacles and weaker irradiationinduced obstacles, the superposition law fallsbetween linear and root sum square limits. Thusfor a given a, the net Ao, decreases withincreasing cr,. (see Equation 6-4 below). As asimple example, taking a. as 200 and 35 MPafor CM5 and CM29 respectively and assuminga normal CRP superposition parameter of e =0.4, a common , = 95 MPa results in a ao, of51 (CM15) vs. 78 MPa (CM29), respectively.These are close to the observed values.

Table 4-1 summarizes the trends discussed in theprevious paragraphs. Note the magnitudes givenare illustrative for 290°C, 0.5xIl2 n/m2 low-to-intermediate flux irradiations of intermediate-to-high copper alloys in the standard stress reliefcondition. The specific values must be viewed asrepresentative, since detailed behavior dependson the entire combination of variables.

4.1.2 Low Copper Alloys

Figures 4-5a, b and c plot Aa, from the T14 andPB capsules versus phosphorous content (0.002to 0.047%) for low copper (0.02%) CM alloyswith low (0.01%), intermediate (0.86%) andhigh (1.53%) nickel. The effects of increasingnickel are shown in Figures 4-5a (low, CM1, 2),5b (intermediate, CM3, 4, 5) and Sc (high, CM6,7), respectively. The Aa, increasesapproximately linearly with phosphorous in allcases, hay(P) = A + BP. The slopes of Ay(P)range from B = 550 to 1450 MPa/%P. Plots ofthe B versus nickel shown Figure 4-5d do notseem to show any systematic trend. However, thedata from the T14 capsule are more scattered,and the high nickel point seems to beanomalously low. The slopes average 1165MPa/%P with the T14 point included, and 1285MPal%P if it is deleted. Figure 4-5e comparesthe A,(P) for alloys with two copper levels(0.02% and 0.11%). The effect of phosphorouson A&Y for the PB capsule (filled symbols) isvery similar in both cases. However, the apparentphosphorous sensitivity of the T14 capsule datais higher for the alloy with 0.02% copper andmuch lower for the alloy with 0.1 1% copper,with B = 1931MPa/%P and 0 MPaJ%P,respectively. Again, these differences may besimply a consequence of the larger scatter in thesteels in the T14 capsule. Alternately it mayindicate that higher copper decreases the effectof phosphorous for steels in the standard stressrelief (T14) versus as-tempered (PB) condition.

The effect of nickel on low (0.02%) coppersteels was shown in Figure 4-5a to 4-5c. Crossplots of the CM data are shown in Figure 4-6 forlow (Figure 4-6a) and high (Figure 4-6b)phosphorous. In three out of the four cases theAcS, shows a clear linear trend, Aa(Ni) = A +BNi, with an average slope of B = 20*4MPal%Ni. The slope for the high phosphorousT4 capsule data is much less (5.4 MPa/%Ni) andthe individual AoY are more scattered. Given thegeneral scatter of the Ao, values, suchdifferences are not unexpected. If this data pointis included the nickel sensitivity slope decreasesto 16 MPa/%Ni.

28

Table 4-1. Summary of Compositional Dependence of Hardening in High Copper Steels

Variable Dependence Interactions Magnitude

copper threshold- nickel, manganese, - 50 MPa (0.0%Ni)*saturation HT't (S - 150 MPa (0.8%Ni)*sigmoidal section ) - 240 MPa (0.8%Ni)*

*@ 0.3% Cu

nickel - A + BNi copper, managnese, B - 110 MPa%Ni

HT (see section 5)

manganese - A + BMn copper, managnese, B - 30 MPa/%Mn

HT (see section 5)

molydebdnum not established superposition of the - -30 MPa with vs.irradiated/unirradiated without molydebdnum

obstacle strengths

boron, not established probably minorchromium

tHT=heat treatment

Figure 4-7 plots Au. of low (0.02%) copperCM alloys (CM8, 3, 9) from the T14 and PBcapsules versus the manganese content. TheAs, data scatter around a linear trend,Ayy(Mn) = A + BMn, with a slope of B = 10±1MPa/%Mn.

Figure 4-8 shows histogram plots of Aa fromthe T14 and PB capsules for alloys with singleelement compositional variations. Theseinclude: low (0.02%) copper CM alloys(CM23 to 27) with a) low (0.05%),intermediate (0.15%) and high (0.3%) carbon(CM23, CM3, CM24), b) high nitrogen(CM25), c) doping with a mix of trampelements (CM26) and d) a boron addition(CM27). There is no systematic trend withcarbon. The intermediate carbon base alloy(0.15%, CM3) has the highest As;, in one case(PB) and lowest in the other (T14). A slightincrease in Aay at the higher nitrogen level(CM25) is observed in data from bothcapsules. The alloy with the boron addition(CM27) has a lower Acr in both cases. TheAy of the alloy with tramp element additionsis the same as the base alloy in one case (T14)and slightly less in the other (PB). However, all

these A;o are small and the differencesbetween them are even smaller. Thus theeffects of these composition variations, withthe possible exception of boron, can beconsidered to be well within the data scatter.Since boron additions both-reduce themagnitude and increase the scatter in theunirradiated cr, no firm conclusion can bedrawn regarding the effect of this elementeither. Therefore, it is concluded that theeffects of these other composition variationsare minor and, if they exist at all, will emergeonly at higher fluence, where the matrix defectcontribution to A,is larger.

Table 4-2 summarizes the trends discussed inthe previous paragraphs for low copper (-0.02%) steels. Again, the magnitudes given areillustrative for 290°C, 0.5-lx102 n/m2irradiations (assuming there is no flux effect inthis case) of low copper alloys. The effects ofheat treatment have not been determined. Thespecific values again must be viewed asrepresentative.

29

125

100

.075

50 1

25

0 0.01 0.02 0.03 0.04 0.05

P (wL %)

It

0 0.01 0.02 0.03 0.04 0.05

P(wt. %)

0 0.01 0.02 0.03 0.04 0.05

P (WL %)

0 0.5 1 1.5 2

Ni (%)

12

10

7

2

4

0

PB - 0.0% Cu

PB-0.1%Cu

T14 - 0.0% Cu

T14 - 0.1% Cu

5 a e

0.

5 .

o @

4

CM -O .8%NiA A, . . .

0 0.01 0.02 0.03 0.04 0.05

P(wL%)

Figure 4-5 Variation of Aoy with P for a) low copper, low nickel; b) low copper, intermediatenickel; and c) low copper, high nickel steels. d) Variation of phosphorous sensitivity (B)

with nickel. e) Comparison of Acy (P) for alloys with 0.02 and 0.1 1% copper.

30

125

100

75

50

25

0

-25

125

100

ft

* T14 b

9 PB

*~

CM-0.8%Ni0 2 -- - I __

I

S

* T14 a

* PB 9 .

.~S

CM - 0.005%P

0 0.5 1 1.5 2 0 0.5 1 1.5

Ni (wL %) Ni (wt. %)

Figure 4-6 Variation of Aay with nickel for a) low and b) high phosphorous steels.

0 0.5 I

Mn (wt. %)

Figure 4-7 Variation of ATy with manganese for low copper CM alloys.

31

75

50- I-

.3 25

7% - --A.

2

75

50

254

01

* T14

* PB

CM - 0.8%NiI II

-251.5 2

_ _ _ _ _ _ ._ _ _ _ .

50

40

iY3

C4

30

20

10

- L .. L... I * 1. Ii.1 1 O1 I I[ I I[ I

U U z X P

Figure 4-8 Variation of Acy with carbon, nitrogen, boron and tramp elements (TE) forlow copper CM steels.

Table 42. Summary of Compositional Dependence of Hardening in Low Copper Steels

Variable Dependence Interactions Magnitude

phosphorus - A + BP possibly copper and B - 1200 MPa/%P_ _ _ _ _ H T _ _ _ _ __H T

nickel - A + BNi B - 20 MPa/%Ni

manganese - A + BMn B - 10 MPal%Mn

C, N, B, tramp not established probably minorelements

32

5 ANALYSIS OF THE COMPOSITIONAL TRENDS

5.1 Comparison of the IVARResults With Predictions of theNUREG/CR-6551 Model

The NUREG/CR-6551 AT model (referred tohere as the NUREG model) derived fromstatistical fits of physically motivatedembrittlement equations to the PREDB, providesa good basis to analyze and evaluate the datatrends described in the previous section. TheNUREG-AT model was first converted to acorresponding NUREG-&a, model using ananalytical AT-Aca, relation. Details are given inAppendix A. Figure 5-1 shows the predictedversus measured h,o for data from the Tl4capsule. The predictions are based on theNUREG-AT model parameters for welds. Goodagreement is found for all the LV and CMmodel steels as well as the welds and platesobtained from various sources. The overall biasand standard error between the predicted andmeasured values are about -1.9 and ±18 MPa,respectively. A least squares fit has a slope of1.06 and an intercept -6.1 MPa. Thus the meanNUREG-&F, model predictions are within about6 MPa of a perfect 1: correlation withmeasured values up to 200 MPa.

Figure 5-2 compares the NUREG-&AG modelpredictions of copper dependence of A, withthe T14 data that has been adjusted to acommon nickel (0.8%) and phosphorous(0.005) content. The adjustments are based onthe differences predicted by the NUREG-A;7model for the common versus actual alloycomposition. These adjustments are smallexcept in cases where the nickel level is muchdifferent than about 0.8%. No correction ismade for manganese differences. The CM and,-LV model steels, with nominal nickel andmanganese contents of about 0.8% and aboutIA to 1.6%, respectively, are shown as the filledcircles. The CM and LV steels with higher orlower nickel and manganese are shown as theunfilled circles. The other welds and plates areshown as unfilled diamonds and triangles,respectively. The agreement is generally good.

However the Aa3, of the intermediate nickel, highmanganese CM and LV alloys fall a little higherthan the NUREG model predictions in the rangeof 0.2 to 0.4% copper. As might be expected,the hs, for the low manganese CM alloys fallbelow the NUREG model predictions.

Figure 5-3 compares the NUREG modelpredictions of the effect of nickel on Acy withLV and CM data from the T14 capsule. Boththe magnitude and predicted variation of Aywith nickel are in good agreement with the highcopper (0.42%) data (CM18-20) shown inFigure 5-3a. The agreement is not as good forthe intermediate copper (0.22%) CM alloys(CM1 5-17) where the Ar, are underpredicted atboth intermediate (0.85%) and high (1.6%)nickel levels (CM 16 and 17).

Figure 5-4 compares the NUREG modelpredictions of &F. as a function of fluence todata for low copper (0.02%) intermediate nickel(0.85%) CM alloys (CM3,5) for low and highphosphorous levels. In this case Acr, data fromlower fluence2 capsules have been added to T4,T14 and PB results. The data are scatteredaround the NUREG predictions, but overallagreement is good. Thus, the IVAR AGy datasuggests that the effect of phosphorous is wellrepresented by the NUREG model.

Given various sources of uncertainties in the dataand application the Acrmodification of theNUREG AT correlation model statistically fit tothe completely independent surveillance PREDB,the overall agreement is remarkable. Thus theACF, database generated in this study provide apowerful and independent confirmation of thegeneral form of the NUREG model.

2 These capsules are designated TI, T2. TI I-T13, and T21

33

300 1 1 5T14

-~~~~ ~0200

40

0

0 100 200 300

Acy (pred, MPa)

Figure 5-1 Comparison of the NUREG- Acy model predictions with the data from the capsule T14.

200

150

100P4

bcX

50

0

- NUREG

0 CM/LV Base

O Weld

a Plate

0 CM/LV Other

0.00 0.20 0.40 0.60 0.80 1.00

Cubk (%)

Figure 5-2 Comparison of the NUREG- Aay model predictions with the data from capsule T14adjusted to 0.8 nickel and 0.005% phosphorous.

34

400

0 0.5 1 1.5 2

250

200

150

100

50

0

Ni (wiL %)

0 0.5 1 1.5 2

Ni (wt. %)

Figure 5-3 Comparison of the NUREG-Acy model predictions of nickel dependence ofembrittlement with the T14 data for a) 0.4% copper and b) 0.2% copper steels.

0 0.5 1 1.5

*t (1023 n/n 2 )

Figure 5-4 Comparison of NUREG-Ahy model predictions with Acry data as a function of fluencefor low copper (0.02%) intermediate nickel (0.85%) CM alloys for both low (0.005%,

CM3) and high (0.04%, CM5) phosphorous levels.

35

125

100

75

50

es

tra4

25

02

300

52 The Microstructural Basis,Mechanisms and Models for theComposition Dependence ofHardening and Embrittlement

The primary cause of AT is irradiationhardening, A, [Odette et al, 1985; Fisher andBuswell, 1987]. Hardening is in turn caused bythe irradiation induced formation of a largepopulation of nanoscale features that act asobstacles to dislocation slip.[Odette, 1983;Odette and Lucas, 1998; Fisher and Buswell,1987]. The irradiation-induced nanofeaturesare significantly weaker than strong, pre-existingobstacles to dislocation slip, such as fine scaleMo2C carbides, that are largely unaltered byirradiation. The latter require dislocations tobow around them, while dislocations canpenetrate the irradiation nanofeatures. Theindividual strength contribution of thenanofeatures (,) is a function of their specificcharacter, size [rJ, number density (Ni) andvolume fraction (f1) as [Odette and Lucas, 1998]

Oi - Ai(r1y4f1 (5-1)

where the f, = [47tr, 3 3]N,, and the Ai describesthe strength of the feature that depends on r.Peak strength occurs at roughly r = I to 1.5nm. The Ai(r;) decreases rapidly below this peakhardening size (r1,), and roughly proportionatelyto (rtrj), where n c 1 at larger sizes. Asdiscussed elsewhere in this report, the net AY, isless since, a, must combine with the contributionof pre-existing strong obstacles ((Y.) [Odette andLucas, 1998].

Current understanding of the embrittlementnanofeatures is based on combinations ofsophisticated microstructural and microchemicalcharacterization studies and physical models.Characterization methods include: small angleneutron and x-ray scattering that provide size,volume fraction and compositionalinformation [Odette, 1995; Odette and Lucas,1998; Phythian and English, 1993; Solt et a],1990, 1993; Mader, 1995; Williams andPhythian, 1996; Wirth, 1998; Wirth et. aL 1999;Alexander et. al, 19991, various types of electron

microscopy that provide both high resolutionstructural images and compositional information[Phythian and English, 1993; Jenkins 1994;Williams and Phythian, 1996] and 3-dimensionalatom probe-field ion microscopy that measuresthe configuration of the elements within a smallsampling volume to near atomic resolution[Miller et al, 1993; Miller et al, 2000]. Thermo-dynamic-kinetic models are used to track thetransport and fate of irradiation defects andsolutes and to predict the number, sizedistribution and composition of the nanofeatures[Odette and Wirth, 1997; Odette and Lucas,1998; Odette 1998; Wirth, 19981. For pressurevessel and surveillance conditions and theirradiations in this study, the nanofeatures can bedivided into two broad categories [Odette andWirth, 1997; Odette and Lucas, 1998; Odette,1998; Fisher and Buswell, 1987; Mader, 1995;Wirth 1998; Liu et al, 1997]:

- copper-rich or catalyzed Mn-Ni richprecipitates (CRPsl?Ps)

- matrix features primarily in steels with low orno copper The matrix features are defect(vacancies and possibly interstitials)-solutecluster complexes that are probably formeddirectly in displacement cascades. Otherprecipitate phases, such as phosphides, mayalso contribute to matrix feature hardening.

5.2.1 Copper Rich Precipitates

Following typical heat treatments, copper canremain dissolved in the in the iron matrix up toabout 0.3% [Odette, 1995; Odette and Lucas,1986, 1988, 1997, 1998; Buswell and Jones,1993; Williams and Phythian, 1996; McElroyand Lowe, 1996; English et al, 1997]. However,the solubility of copper decreases at lowertemperatures, to <0.01% at around 290°C. Thesupersaturated copper diffuses and precipitatesinto a separate phase. Enhanced diffusion,caused by excess vacancies produced byirradiation, enormously accelerates processesthat are normally thermally sluggish, resulting inthe rapid formation of a high number (1023m 3 ) of small (-1.5-3 nm diameter) CRPs with a

36

BCC crystal structure that is coherent with theiron matrix.

The CRPs are the dominant hardening feature insensitive steels that have copper contents greaterthan about 0.05-0.1%, which is the minimumneeded for rapid nucleation. The CRP volumeincreases with copper up to an effective upperlimit around 0.3%, imposed by copper pre-precipitation at the final stress relief temperature(typically about 610°C). The CRP contributionhas a relatively weak irradiation temperaturedependence and saturates at high fluence, due tocopper depletion from the matrix. The CRPevolution is delayed at higher fluxes byinterstitial recombination with vacancies that aretrapped at solutes and in small transient clusters[Odette et al., 1993; Odette and Lucas, 1998;Odette, 1998]. The amount of recombinationincreases with increasing flux. At very low flux,CRP evolutions may be accelerated due to acontribution of thermal diffusion to copperprecipitation [Odette et al, 1999].

The precipitates are not pure copper, but areenriched in manganese and nickel as well assmaller amounts of phosphorous and silicon[Mader, 1995; Liu et al, 1997; Odette and Lucas,1998; Odette, 1998; Wirth, 1998; Wirth andOdette, 1997]. The thermodynamics of thecopper-manganese system is such that at lowtemperatures around 290°C manganesepartitions from the matrix and is enriched incopper precipitates. Nickel itself does notinteract as strongly as manganese. However, ifnickel and manganese are both present, theyinteract strongly with each other, andsynergistically increase the concentration ofboth elements in the precipitates. In some casesthis can result in the replacement of CRPs withmanganese-nickel rich precipitates (MNPs) witha small copper rich core [Wirth and Odette,1999; Liu et al, 19971. Manganese-nickelenrichment of the precipitates is promoted byhigher alloy contents of these elements, lowercopper (beyond the amount needed fornucleation) and low irradiation temperature.The increase in the volume fraction of CRPs (orMNPs) with manganese and nickel explains the

strong effect of these elements on increasing AA,and AT.

Typical values for the A, for CRPs at peakstrengthening size are about 3750 MPa. Thus, af,= 3xl0 3 produces a , - 240 MPa. Taking

.= 200 MPa and a superposition parameter ofe = 0.4 (see Equation 6-4 below) typical ofCRPs, gives a net A, - 135 MPa.

Figure 5-5 plots the estimated volume fractionof CRPs from SANS measurements on CM andLV alloys from the PB capsule as a function ofthe alloy nickel and manganese contents. Thecorresponding estimated precipitate volumefractions of copper, nickel, manganese andvacancies (lumped together for clarity) are alsoshown. The composition evaluations areconsistent with the magnetic to nuclear scatteringratios measured in the SANS studies.Thermodynamic model predictions of the CRP(MNP) composition are used to guide thisassessment [Wirth, 1998]. The thermodynamicmodel generally predicts higher nickel andmanganese levels in the precipitates than isconsistent with the experimental scattering ratio.Thus the amounts and relative proportion ofthese elements are minimally adjusted to provideconsistency. The resulting estimates of thecomposition of the precipitates are not uniqueand are subject to considerable uncertainty.However, these estimates are reasonable andcertainly provide insight into the general trends.Further details are given elsewhere [Wirth, 1998;Wirth et al, 19991.

Figure 5-5a shows differences in the precipitateparameters as a function of nickel from 0.02 to1.69% for the CM alloys (CM 18, 19, 20). Thef, increases linearly with nickel. Higher alloynickel levels increases the CRP manganese andnickel contents, with a big jump between 0.84and 1.69%. Indeed, at highest nickel theprecipitates are actually manganese-nickel rich(MNP). Figure 5-5b shows similar but moremodest increases that are observed for the LValloys with 0.85 to 1.25% nickel (LC, LD).Similar effects of increases in the CM alloymanganese content from 0 to 1.6% (CM21, 19,

37

1.

* CRP

Ni

v Cu

* Mn + Vac.

I .v

0.81

a 0.6

0.4

0.21

0. -

0.00.5 1.0 1.5 2.0

Ni (%)

0.5 1.0 1.5

Mn(%)

* CRP

Ni

Cu

A Mn + Vac.

I

2.0

0.5 1.0Ni (%)

1.5 2.0

0 100 200 300

A% (pred., MPa)

Figure 5-5 Volume fraction of CRP's estimated from SANS measurements on CM and LV alloys forthe PB capsule as a function of a) nickel for CM alloys, b) nickel for LV alloys, and c)manganese for CM alloys; d) comparison of measured Acy with values predicted from

SANS microstructural parameters.

38

r1.0

0.8

aCM 0.4% Cu 0

. i.A

.(a. -

0.6r

0.4

0.2

0. 00.0

LV - 0.4%Cu b

0 * OVV

AA

I1.n,.

0.8 1

0.5 -

0.C0-0.0

CM 0.4% Cu c

v Y

A

A , 9

v

0.2t

22) are shown in Figure 5-5c. ligher nickeland manganese alloy contents also increaseN,p [Wirth, 1998]. In this study, the increasein N,p is more than a factor of 7 between 0and 1.69% nickel, with a correspondingreduction in r, from - 2 to 1.4 nm. Figure 5-Sd compares the Aay predicted by a hardeningmodel based on the SANS measurements off, and r,, to experimental values. Details ofthe procedure are described elsewhere [Wirth,1998; Wirth et. al, 1999]. The agreement isgood, demonstrating that the effects ofmanganese and nickel on the CRPcontribution to hardening and embrittlement,as summarized in Table 4.1, can beunderstood on the basis of the correspondingeffects of these elements on the f, and r,.

52 Matrix Features

The matrix features are generally not as wellunderstood as CRPs. Atom probe studies haveshown regions enriched in solutes likemanganese, nickel and silicon [Pariege, 1994;Miller et. al, 2000]. These features areprobably formed directly in cascades, wherethe solutes are complexed with defect clusters[Wirth, 1998; Wirth and Odette, 1999].Vacancy cluster solute complexes are the mostlikely candidate, although small interstitialcluster-solute complexes are also a possibility.Even if the defect clusters dissolve, or migrateto sinks, the solute enriched regions are left intheir wake. The atom probe studies suggestthat about 2.5x IO' matrix features form per1023 n/M2 (roughly I for every 10 cascades).Assuming an effective r, - 0.7 nm and f,, -5x 04 per 1023 n/M

2, as suggested by SANS

studies [Wirth, 1998] (although the size of theactual enriched region may be larger) resultsin an estimate of A. 1 - 1350 MPa. Since thematrix features are significantly weaker thanCRPs, it is generally assumed that their entireG, contributes (adds) to Sar Thus the matrixfeatures are expected to produce about 30MPa hardening at 102 ntn 2. Since the numberof matrix features increases in roughproportion to fluence (t), at a roughlyconstant size, their contribution to M ispredicted to increase with 'Jt. Note that given

their typical concentration and composition,depletion of matrix manganese and nickeldoes not lead to a saturation of the matrixfeatures in the fluence range of interest.However, a slow decrease in the fluenceexponent in the NUREG model can beunderstood based on depletion and overlapeffects, as well as some thermal recovery of thestrengthening contributions of the matrixfeatures over long periods of time.

At low concentrations phosphorous may alsosegregate to the matrix feature complexes.However, phosphorous has a very lowequilibrium solubility in steels that can formalloy phosphides like Mo3P, which are muchmore stable than the Fe3P phase in binaryalloys [Odette, 1998]. Thus alloy phosphidesare expected to form and contribute to AcrFine scale features containing phosphorous,nitrogen and carbon have been observed inatom probe studies [Pareige, 1994, Miller2000]. Phosphorous also interacts stronglywith copper, and segregates to CRPs.Phosphorous gettered by CRPs is not availableto form phosphides. This rationalizes aninteraction that reduces the effect ofphosphorous at higher copper levels. Aphosphorous-copper interaction of this sortcan also be produced by the strengthsuperposition mechanism noted previously.That is the individual strength contribution ofphosphides to the net Acs, is reduced in thepresence of CRPs.

As noted above both SANS and atom probestudies have detected matrix features, eitherdirectly (atom probe) or through scatteringresponses (SANS), that indicates a role ofmanganese, nickel and phosphorous. Further,atom probe studies of samples from thedecommissioned CHOOZ reactor vessel havebeautifully quantified the number and generaldilute solute enrichment characteristics ofmatrix features over a wide range of fluence[Pariege, 1994, Auger et al, 1994]. Whileefforts to better quantify the matrix featuresare continuing, these observations, and others[Wirth and Odette, 1999], clearly rationalize

39

the Aa, trends with these elements assummarized in Table 4-2. That is, higheralloy nickel, manganese and phosphorouscontents increase some combination of thesolute content, volume fraction and strength ofthe matrix features, leading to increased Aay.It should be noted that the role ofphosphorous is somewhat special, since well-formed phosphide precipitates may beresponsible for the hardening caused by thiselement. Further, depletion of matrixphosphorous would be expected to lead to aneventual saturation of the phosphide matrixfeature contribution. However, the evolutionof the phosphides appears to be much slowerthan characteristic of CRPs, consistent withtheir narrow range of chemistry and the lowphosphorous concentration. Thus forpractical purposes, it is a reasonableengineering expedient to lump them with theother matrix features.

More detailed discussions of the experimentaland modeling that underpins the precedingdiscussion can be found elsewhere [Odette andLucas, 1998, 1999; Odette, 1998; Eason et al,19981 and will be elaborated on in futurereports. For the present purposes, however, itis sufficient to conclude this section by notingthat all the major trends in both the NUREGmodel and observed in the IVAR database areconsistent with current understanding ofembrittlement mechanisms. However, anumber of open questions and unresolvedissues remain, providing further opportunitiesfor improvements in the NUREGembritlement correlation models. These arebriefly described in the following section.

5.3 Discussion of Improvements inthe NUREG EmbrittlementCorrelation Model Treatment ofComposition Effects

It must be stated at the outset that it is notpossible to separate compositional effects onembrittlement from other metallurgicalvariables, such as product form and heattreatment, and irradiation variables, including

flux, fluence and temperature. Some of theeffects of heat treatment are presented in thefollowing section. Thus, a comprehensivereassessment of the NUREG models andprogeny correlation models will be based onthe on the entire IVAR database in the future.Nevertheless, the information presented in thisreport provides some insight into what suchimprovements may entail.

First, the overall treatment of copper-nickelinteractions in the NUREG model seems fairlyrobust. However, IVAR data indicate thatmanganese is also a key element in the CRPcontribution to embrittlement. This may atleast 2artlv explain why the forging CRPcoefficient (700C) is lower by about 22%compared to that of plates (95 0C). Assumingtypical copper, nickel, and phosphorouscontents of 0.15%, 0.6% and 0.01%,respectively, and an irradiation fluence of5x1022nrn2 at 2880C, the NUREG plate modelpredicts a Acy1, of about 70 MPa. However,forgings have about half the manganesecontent (- 0.7%) as plates (-1.4%). Based oncoefficients in Table 4-1 this translates to areduction in Aayby about 20 MPa, or a 29%reduction.

There are even larger differences between theNUREG CRP coefficients for forgings andwelds; and manganese differences do notexplain differences between the NUREG plateand weld CRP coefficients. However, theIVAR AF data for the CMILV steels and thewelds and forgings do not indicate such largedifferences. Other factors that may influencethe apparent product form sensitivity includethe variations in both the average and range ofcopper content in the PREDB, which aresignificantly higher for welds. Effects that arenot accounted for in the NUREG model, suchas an influence of copper and nickel on thefluence dependence of &T, and the effects ofstart-of-life Charpy properties on the ,Ac/ATrelation, may also play a role in apparentproduct form sensitivity. Further, a number ofother variables are known to influence bothCRP microstructures and W, at an otherwise

40

specified set of conditions. These variablesinclude: a) a range of heat treatment effects(see below); b) phosphorous and silicon, whichare enriched in CRPs and increase theirnumber densities; and c) coarser scaledislocation sink microstructures whichinfluence the radiation enhanced diffusion rate- hence, the fluence dependence - of theCRP contribution [Odette and Lucas, 1998;Odette, 1998]. Finally, the current IVARdatabase shows that flux and compositioninteract to influence CRP contributions to ArData on such interactions will be extended toirradiation temperature in the future.

In summary, the part of the IVAR databasepresented here provides a partial basis tonarrow differences in the CRP contributionnow empirically attributed to a product formarising from mechanisms that are notunderstood. More importantly, these resultslead to the anticipation that, in the future, suchdifferences can be further reduced andexplicitly modeled to reflect the responsiblevariables.

Similar arguments pertain to the matrix featurecontributions to Ao. Clearly some of theproduct form variability in the NUREG modelcan be attributed to variables that are notexplicitly treated. Manganese and nickelenhance hardening but are not accounted forin the matrix feature contribution in theNUREG model. Figure 5-6 plots the lowcopper LV and CM A;, data (LG, CMltolO)from the T14 and PB capsules versus a matrixfeature solute chemistry factor (CF.,) simplydefined by scaling the results as shown inTable 4-1 by dividing by 10, where

CFf = 120P + 2Ni +IMn (5-2)

The PB data correlate very well with CF,(filled circles) while the T14 data (opencircles) follow a similar trend, but are morescattered. In both cases the least squares fit tothe Aa,(CF,,) have a negative value at the CF.,= 0 intercept, suggesting that there is athreshold solute concentration for hardening

in low copper steels. However, it is not clearthat this is actually the case, as illustrated byVM-series data from the PB capsule shown asthe open diamonds at CF., = 0. These VMalloys do not contain manganese and nickelbut do include small concentrations ofnitrogen and in one case a 0.25% titaniumaddition.

The A;y data from the PB capsules for othersimple VM-series alloys shown in Figure 5-7also illustrate the role of solutes and soluteinteractions on matrix hardening. Theunalloyed iron (VA) with low (10 ppm)nitrogen has a Acy of 42 MPa. Increasing thenitrogen to 100 in unalloyed iron (VK, W,VW) has little effect on hardening with anaverage A;, of 36 MPa. However, the a; forthe VB alloy with 40 ppm nitrogen and 1%manganese increases to 102 MPa. The VRalloy with 120 ppm nitrogen and 1%manganese has an even larger Ay of 152 MPa,suggesting a strong interaction between theseelements. In contrast the VC alloy with 0.15%carbon, 30 ppm nitrogen and 1% manganesehas an intermediate A; of 70 MPa. Most ofthis reduction (- 24 MPa) can be attributed tothe precipitation of manganese inFe(0.2Mn)3C phases, and a lesser amount (- 8MPa) is estimated be due to the lower nitrogenin this steel (VC) compared to the 1% Mnalloy without carbon (VB). Without nitrogenpresent the effect of manganese is estimated tobe small (_10 MPaJ%Mn), but similar to thatfound for RPV steels in Table 4-2. The VBalloy with 40 ppm nitrogen and 1%manganese showed a strong SANS signalsimilar to scattering from matrix features incomplex steels [Wirth, 1998]: a radius of about0.76 nm, a volume fraction of 0.052%, and alow magnetic-to-nuclear scattering ratio(0.57). This scattering ratio is characteristic ofmanganese-vacancy clusters.

Such subtle interactive effects rationalize thevery large relative scatter in matrix features,A;, and AT that are observed in low coppersteels. The scatter in AT is illustrated in Figure5-8a, comparing the NUREG matrix feature

41

predictions with the data from the Frenchpower reactor surveillance program [Brillaudand Hedin, 1992]. Figure 5-8b shows thelarge scatter also observed in Ac, in the lowcopper steels irradiated in the IVAR capsules,including an apparent difference between theLV and CM alloys of unknown origin. Thesignificance of this scatter has been discussedelsewhere [Odette and Lucas, 1999]. Briefly, itis not of much practical significance in lowcopper steels which experience only small tomodest AT. However, since the matrix featuresadd to the CRP contribution, presumablyalong with its attendant scatter, this variabilitymay be much more serious in sensitive highcopper and high nickel steels. This is ofparticular concern at high fluence, where the

125

100

75

50

25A

0

- 0

0.I I

0

0 1

-250 2.5 5 7.5 10

CFmf

matrix feature contribution becomes moresignificant. Indeed, based on theseconsiderations it has been shown that AT inexcess of upper bound estimates from theNUREG model based estimates might beanticipated in some cases [Odette and Lucas,1999]. However, this potential non-conservatism may be mitigated by thesimplified treatment of phosphorous in theNUREG model. In particular both synergisticinteractions with copper and phosphorousdepletion at high fluence would reduce actualAT compared to the NUREG modelpredictions. Additional data generated in theIVAR program will help to resolve theseissues.

* CM-T14

O0 CM-PB

A VM-PB

12.5

Figure 5-6 Variation of Aay with a matrix feature chemistry factor given in Equation 5-2for low copper CM and LV steels for capsules T14 and PB. The unalloyed VM steels are shown as

filed triangles.

42

200

150

100

50

0 z .2 .2

':4

zZ Z

:4._I. >

Figure 5-7 Acy for various V-series alloys with no copper irradiated in PB.

'-- Plate MF i

'-Weld MF !0 plate

a weld

CM

LV

0 0.25 0.5 0.75 1 1.25

4 t (1o23 n 2)

Figure 5-8 a) Comparison of NUREG matrix feature predictions with low copper French powerreactor surveillance data; b) plot showing scatter in Aay in low copper steel irradiations

in this study and unexplained differences between CM and LV alloys.

43

V-PB 0.0%Cu

HinF]

100

7S

0

I.- 50

25

18.0 18.5 19.0 19.5 20.0

Log t(lO1 9IrdCM2 )

- - l

6 EVALUATION OF THE MATRIX COPPER CONTENT

A key issue in developing embrittlement modelsis determining the amount of copper in solution,thus available for precipitation under irradiation.Bulk copper (Cu.) that is tied up in coarseprecipitates, or other phases (e.g., copper sulfideinclusions [Fisher et. al, 1985; Fisher andBuswell, 1987]), at the start-of-life does notcontribute to subsequent hardening andembrittlement. The difference between Cu, (inwt%) and effective dissolved, or matrix, coppercontent (Cu.) is deternined by both the alloycomposition and heat treatment history. Pre-precipitation of large E-phase copper particles,primarily on dislocations, during tempering andstress relief (SR), is a primary mechanismcontrolling Cu. below bulk levels. The Cu.,approaches thermodynamic solubility limitsafter long times at around 600°C. However,thermal precipitation is a complex process. Aswell as time-temperature kinetics, alloychemistry (thermodynamics) and microstructurelikely influence pre-precipitation behavior. InNUREG/CR-6551 a statistical fit to the overallPREDB gave the maximum Cu., (Cu.) of 0.3%.This result is broadly consistent with data trendsand various estimates in the literature, althoughboth higher and lower values have been reported[Odette, 1995; Odette and Lucas, 1986, 1988,1997; Buswell et al, 1993, Williams andPhythian, 1996; McElroy and Lowe, 1996;Williams and Phythian, 1996; Kenway-Jacksonet. al, 1993; English et al, 19971. Indeed, bothinformation in the literature, and more recentanalysis of the PREDB, have suggested that theactual value varies, depending on the alloynickel content [McElroy and Lowe, 1996;Odette and Lucas, 1990, 1998; Williams andPhythian, 1996].

Accurate direct estimates of Cu. require detailedand costly measurements that push, or evenexceed, the capabilities of state-of-the-artmodern microanalytical characterizationmethods. While some of these studies have beencarried out, much more work will be required toprovide a useful microanalytical databasenecessary to develop models for Cu.. However,

mechanical property changes are the issue ofprime concern and can provide indirectestimates of matrix copper. Thus, the variablestress relief (VSR) study was primarily intendedto conveniently assess the effects of the heattreatment and nickel content on Cu. by simplyassessing the corresponding effects on Ay.While this objective was largely achieved, theresults of the VSR study also showed that heattreatment effects extend well beyond matrixcopper levels, and influence both the start-of-life properties and microstructures of RPV steels.The start-of-life condition, in turn, affects theirradiation-induced changes in mechanicalproperties.

The use of a large set of small split-melt modelsteels with a wide range of compositions andheat treatments in the VSR study resulted inconfounding effects that complicated assessmentof Cu. in a fraction of cases. The complicationsincluded large o variations and variability(scatter) for some heat treatments. These t,variations also reflect underlying microstructuraldifferences. These problems were exacerbatedby the effects of banding and ghost lines foundin a number of the CM forgings, coupled withthe use of a slow cooling schedule of about8°C/h. The as-tempered alloys and the CMalloys that were furnace cooled following stressrelief were more stable and less variable.

Thus for purposes of assessing the matrixcopper, the VSR Au, data were carefullyscreened to avoid or minimize the confoundingeffects noted above. The screened VSR datawere used to assess the Cu, based on theNUREG model. The NUREG-AT model wasfirst converted to corresponding Au, predictionsusing analytical &T-ME, relations (see AppendixA). The NUREG-Aa. model was then used tocalculate values of Cu. for the VSR data set aswell as alloys subject to different heat treatmentsin the PB experiment, consistent with themeasured Acr, for the specific alloy andirradiation condition (phosphorous, nickelcontent, flux, fluence and temperature). Other

44

modifications of the NUREG-&i. model toaccount for flux-composition and product formeffects are discussed below.

A second approach to estimating Cu. from theAs, data was based on examining deviationsfrom the NUREG model form

AaF= A + BX (6-1)

where X is the NUREG copper factor, X = 0 forCu, 0.072% and X = (Cu.-0.072)h 7s for Cu.> 0.072%. In this case, no assumptions weremade about A and B, or their dependence onembrittlement variables. The A and B werefound by fitting the A;y data from sets of alloyswith different copper levels, but nominallysimilar compositions and heat treatment. Minorcorrections were made for nickel differences inthe LV alloys (LG, Li at 0.74% vs. LI with0.85%). The fits to Equation 6-1 were restrictedto alloys with copper levels below the maximumprecipitation limit L. 0.22% for the standardstress relief condition and S 0.33% for the as-tempered condition). The A and B fits were thenused with the measured A; for higher coppersteels (not used in the fitting) to calculate Cu. as,

Cu. = [(A - A)IBl]'5+ 0.072 (6-2)

The second method was applied to A, from theT4, T14 and PB capsules as well as someaveraged data from the VSR study.

The A&-based estimates of Cu, werecomplemented by several other sources ofmicroanalytical information including fieldemission scanning transmission electronmicroscopy (EGSTEM), Seebeck coefficient,electrical resistivity and small angle neutronscattering (SANS) measurements. TheFEGSTEM provides direct evaluation of the Cu.subject to uncertainties and assumpfions used inthe analysis. The Seebeck coefficient (S) andelectrical resistivity (p) evalutions were alsobased on deviations from low copper lineartrends in S and p plotted against Cub, indicatingpre-precipitation. The limited SANS dataprovided direct evidence of the effect of stress

relief on the volume fraction of CRP's from thePB experiment.

6.1 General Effects of HeatTreatment on cy and Ay

To provide a proper framework for assessingCu., it is necessary to begin with a description ofthe general effects of heat treatment on a, aswell as possible effects of ;, on Ac;y. Thisprovides a basis to identify the subsets of datathat can be used most reliably to estimate Cu.As is a general characteristic of quenched andtempered low alloy steels, the ;. in RPV steelsdecreases with increasing stress relief time (tr)and temperature (T.). This trend is shown inFigure 6-1 where the a, data from the VSRstudy are plotted as a function of a temperaturecompensated time parameter Pn defined as

Pn = iexp(-260,000RT.(i))t.(i) (6-3)

Here T. is in °K, t,, is in h and i represents Tk-tincrements of 8°C-lh at the various stages of theheat treatment, including the 660°C-4h temper,the actual isothermal ,-T,,stress relief andsubsequent slow cooling that was truncated at450°C. For most stress relief conditions, the ;,is well behaved; but substantial softeninggenerally occurs at high PT,. However, in somecases a large decrease in a, is observedindicating instability in the alloy microstructure.Such instability is indicated by the data belowthe horizontal lines in Figures 6-la to 6-1c. Thereasons for such large reductions in c are notknown.

Thus the following question must be addressed.Does the lower cr affect Ay due to mechanismsthat are not related to copper pre-precipitationand Cu.? Figure 6-2a illustrates the generaltrend to lower A:, with increasing c, for the setof high copper (- 0.42%) CM alloys withvarying nickel content. The effect is minimalfor the low nickel (0.0%) CM18 alloy and onlyapparent for the lowest (,data in the case of theintermediate nickel (0.85%) CMl9 alloy.However, the trend appears to be moresystematic for the high nickel (1.69%) CM20

45

alloy. Since all these alloys contain more than0.4% copper, pre-precipitation probablycontributes to the a,-aG trend in this case.Figure 6-2b shows similar plots for intermediatenickel (-0.85%) alloys with 0.22% (CM16) and0.33% (CMI 1) copper levels. Both alloys showa trend of lower Aa, with increasing a, at leastfor the highest and lowest a,. However, little orno pre-precipitation is expected in CM 16, withonly 0.22% copper. Thus other explanations ofthe a,-Aa, trend must be sought in this case.Possible reasons include:

1. Random variations in the ay of the specimensused for both the unirradiated baseline andirradiated testing produce random scatter inboy. However, corresponding plots of aY,versus Aa, will show an apparent bias of thetype observed in Figure 6-2. The apparentbias increases with the scatter in aY,. Since thenumber of redundant tests in the VSR studywere limited, and in some cases the scatterwas rather large, such apparent bias is to beexpected. The scatter in ay adds to the scatterin Ar, and the Cu. derived from AO.However, the apparent bias does not directlyconfound assessment of trends in heattreatment effects of Cu,.

2. The individual contribution of the irradiationinduced features (ai) is less than Aa,, since amust combine with other pre-existingdispersed barrier contributions (a.). The a.strength component is due to fine scalecarbides and dislocation intersections that arestrong obstacles dislocation slip. Thecarbides coarsen and the dislocations recoverwith increasing Pn, thus decreasing thenumber of pinning points and a,. Thesuperposition of the cs. and a strengthcontributions falls between linear and rootsum squares laws as [Odette and Lucas, 1998;Foreman and Makin 1967]

Aa, = Oa,, + (I-O)("2 + a,,2)"- aXE (6-4)

Here 0 (= 0 to 1) is a superposition parameterthat depends on the strength of the weakerirradiation induced barriers, as discussed

elsewhere Odette and Lucas, 1998]. Forexample if a,= a,= 150 MPa, and B = 0.4 (atypical value for CRPs), then As, is only 97MPa. However, if a,, is decreased to 50 MPa,Aa,, increases to 125 MPa. That is, while adoes not change, the net Aa, increases byabout 25% because of the lower cr,. Thesolid line in Figure 6.2b shows the predictedeffect on Aay, of variations in a. from 40 to210 MPa for a,= 185 MPa and 0 = 0.4.Note the (, scale assumes that there are 300MPa of contributions to the total yield stressother than a.. Thus, at least part of thevariation in A, with c,can be understood interms of the strength superpositionmechanism. An increase in AG, with adecrease in a. due to stress relief, potentiallyconfounds estimates of Cu,. based on theirradiation hardening data.

3. The recovery of dislocation structures duringheat treatment can also influence the a, itself.A lower dislocation sink density (pd)

increases the radiation enhanced diffusioncoefficient, thus accelerating CRP growth,shifting the Ma, versus fluence curve down tolower fluence (t). In the simplest case ay -a+ pPd and the ~t at a specified Aa, isroughly proportional to Pd. Thus there anindirect physical relation between Aa, and a,,mediated by p. The dashed line in Figure 6-2b is a crude estimate of this effect for CMI Iin the VSR study. Thus, dislocation recoveryduring heat treatment also potentiallyconfounds estimates of Cu, based on Aa,data.

It must be emphasized that the increases in Aa,due to both superposition effects of reduced (Y.and dislocation recovery leading to faster copperdiffusion are real consequences of longer t andhigher T, Hence, these mechanisms should beconsidered in future research, including theirinfluence on the start-of-life Charpy propertiesand the corresponding relation between AT andAay.

46

IE-14 IE-14 2E-14 2E-14

F1t(h)

IE-14 2E-14 2E-14 3E-14

P ()

3E

a CMi8

* CM16

* CM5

E-14

MI9

* M1II

* CM3

3E-14

600

500

i 400

2 300

20D

1001

* CM20

CM12

* CM13

5E-15 IE-14 IE-14 2E-14 2E-14 3E-14

PTt (h)

Figure 6-1 Variation of a; with PT for a) CM5, 11, 18 b) CM3, 11, 19 c) CM12, 13, 20

47

500

450

400

350

300

250-SE-1

a a

16.18

*OA

t * &

S o

.9 . 9 -

S

500

450

400

e' 350

b

* * ik 6* *4 * n8

0 9

0 A 0

300

250SE-15

c

a

* 9v0 * *o0 0

0 40

9 0

-

. . . .

* CM 18 a* CM19* CM20

: r 0 o .t 4. *s S** . S

EU O

a U---- ~

50 150 250

a 425

350 32575 125

Aay (MPa) Aa. (MPa)

Figure 6-2 Variation of Ay with Y (unirradiated) for a) high (.42%) copper CM alloys, b)intermediate (0.8%) nickel, 0.22% copper alloys.

250 - VSR & PB

200

0150

'100

50

0 p 0 0.--0 0.25 0.5 0.75

* AT

o 590

O 607

1

x

Figure 6-3 Variation of Ay with X for irradiated intermediate nickel alloys.

500

450

400

350

175 225

-a

50 525

However, it is not possible to completelydisentangle . reductions and dislocationrecovery from the effects of copper pre-precipitation at this time. Indeed, this may not benecessary if the viewpoint is adopted that Cu.derived from A:y data is a practical surrogate forall three of these real mechanisms. Nevertheless,the following procedure was used to screen thedata for use in assessing matrix copper levels.

1. In order to mininize the effects of scatter,preliminary hardness measurements weremade on the end tabs of most of the VSRspecimens. Large variations in theunirradiated yield a, and/or differences inend-tab hardness between the specimens usedfor baseline and irradiated testing were usedto screen the quality of the Ac, data, and toeliminate the points of suspicious accuracy.

2. The Ac;y data for alloys showing significantmechanical instability during heat treatment,shown as the open symbols below the dashedlines in Figures 6-la to 6-lc were not used toestimate Cu,.

3. The Ac;, data for alloys that were stable, butthat showed a significant reduction in 0yrelative to the other stress relief conditionsfor a particular steel, were also not used toestimate Cu.. These are shown as the otheropen symbol in Figures 6-la to 6-lc.

The remaining filled symbols in Figures 6-la to6-ic fall within cy and Ac;y quality limits judgedto be useful for estimating the effects of heattreatment on matrix copper. It should be notedthat this is scientifically and practically aconservative approach. Beyond the issue ofscatter, if the other mechanisms contribute someresidual fraction to reducing Acy due to stressrelief treatments, the corresponding estimates ofCu. will be biased towards higher levels ofmatrix copper.

6.2 Estimates of Matrix CopperLevels

62.1 Estimates of Cu. Based on AuDeviations From the Low Copper X irend Line

Results of the evaluation of Cu. based on themethod represented by Equations 6-1 and 6-2are presented first. Figure 6-3 plots the Aay forintermediate nickel (- 0.84%) alloys versus X =(Cu.-0.072)°"", for both the as-temperedcondition and averages for selected points forthe 590 and 607°C stress relieved conditions. Inorder to increase the reliability of the keybaseline comparison data, the as-tempered A6ydata for the VSR study were averaged with thecorresponding data from the PB irradiation at asimilar flux, fluence and temperature. Theseaverages include a small adjustment, based onthe NUREG-AC;, model, to account for minordifferences in fluence (0.85 versus lxl 2 n/in2)and irradiation temperature (288 versus 290°C)for PB and VSR, respectively. The averagevalues for VSR data are for the t, of 48 and 96hat the Tuof 5901C and the t of 24 and 48 h atthe T., of 607°C. The Pn at these two T, span asimilar range. The data points at X = 0 are forthe CM3 and CMIO alloys with CuLi = 0.02%.The as-tempered PB and averaged VSR dataoverlap at lower Cub. The as-tempered PB datafollow a linear trend with X up to approximatelyCubk = 0.42% (CM 19) but the 0.33% copperalloy (CM I ) in the stress relieved conditiondeviates from this trend. The least square fit tothe 'low' copper data (filled symbols and solidline) is Ac,= 20 + 365X MPa. The 'high'copper Ac;y data (open symbols) for CMl2 inboth as-tempered and standard stress reliefconditions and CM 1 I and 19 in the standardstress relief condition fall below the trend line,indicating that Cum < Cubk in these cases.

Table 6-1 summarizes the Cu. found by solvingEquation 6-2, which in this case is X., -[(Ac,(meas.) - 20)/365 and Cu, - X- 25 + 0.072.A similar analysis was carried out for theintermediate nickel CM and LV Aa, data fromthe T14, T4 and PB capsules. The results areshown in Figure 6-4a to 6-4f and the

49

Table 6-1. Estimated Cumfor Intermediate Nickel High Copper CM Alloys in VSR Study

Alloy CUbk Cum- AT Cum-590'C Cu,-607°CCM I 0.33 0.33 0.28 0.28CMI9 0.42 0.41 0.29 O.8CM12 0.43 0.23 0.23

Table 6-2. Estimated Cum for Intermediate Nickel High Copper CM Alloys in Various Capsules

Alloy Capsule Bulk Cu Matrix Cu - SSR Matrix Copperas-tempered

CMIr TT4 F 0.26CMIg TI4 0 : 0.27CM 12 T14 0.86 0.21CM18 T14 0.43 0.22CM20 14 0.42 0.27

LC T14 0.41 0.34_ _

Wr T~1 4 04 0.30_L T1 F _T__1 0.36LK T0.80 0.24Ll1T PB 0.42 0.25_ _

LK PBW- 0.80 0.20LOT= PB 0.42 0.41

1MI PB 0.42 0.43CM 12 PB 0.86 0.44CM18 PB _ 0.35CM20 PB ~ _______OA 0.35CM4I T0 33 0.28_ _

CMI9 T4 0.42 0.29LC T4 0.41 0.25 _

Ll T4 0.42 0.26LK T4 0.80 0.18 _

LO T4 0.41_ 0.34

50

200

150 150

2 100 /i1050 IN Low C/ 0 Low Cu cOr.50 ir E3 Low Cu - 50 0 High Cu

0 High Cu I! LowCu

0 0.25 0.5 0.75 0 0.25 0.5 0.75 1

x x

200 200CM-T4 c d LV-T4

50 Lo a / Low Cu cor.150 00 * Low0Cu50 0 O igh Cu

! Z O~~ High Cu . Low Cu

0 0 .25 0.5 0.75 1 0 0.25 0.5 0.75 1

X 0

CM-PB ;/e 20LV-PB 1 f

.. . 0 0 ' 200/

0~~~O

150 tsr U \ /50 ' o ISOh/

I 0~~~~~~~~

dF 100 F / gr=r40h 6 e100 /

<1 / tsr 8 h O Low Cu

fal [/ O AT 5C j/ES O H figh Cu AT

0 . ,O SR a .o3 Low Cll cor.0 0.25 0.5 0.75 1 0 0.25 0.5 0.75 1

x x

Figure 64 Variation of Acy with X for intermediate Ni LV and CM alloys in capsules T14 (a and b),T4 (c and d) and PB (e and f)

51

200

corresponding estimates of Cu, are given inTable 6-2 for the SSR condition.

6.2.2 Estimates of Cum Based on the VSR AyTrends and the Modified NUREGICR-6551Aay Model

Figure 6-5a to 6-Si summarizes the hay resultsfor the screened data set for the various heattreatment conditions. The dashed line is themeasured Aa for the as-tempered condition tohelp guide the eye to Aa, differences forvarious T, and t. The general trends can besummarized as follows.

1. In the steels with Cu* 0.3%, stress relieffollowing tempering systematically reducesAa.. The strongest effect is seen in highcopper (0.86%), intermediate nickel (0.8%)CMI 2 alloy and the intermediate copper(0.43%), low nickel (0.0%) CM18 alloy.Similar but much weaker trends are observedin the intermediate copper (0.42%), highnickel (1.69%) CM20 alloy. The intermediatenickel (0.8%) alloys, CMI I with Cut, = 0.33%and CMI9 with Cu,,= OA2%, fall in between.There is also a general trend towards largerAoYat higher T. in CM12, CMl9 and CM 20.In the cases of CMI9 and CM20, the A, forthe T, = 641 °C stress relief are similar to theAC. for the as-tempered condition. The effectof t is clearest for the CM 19 alloy for T.from 590 to 6240C. This trend is also seen insome other cases (CMI I at 607 and 624°C,CMI 8 at 590°C), but is reversed, or within thescatter, for the other high copper alloys andheat treatments.

2. For the intermediate nickel (-0.85%) lowcopper alloys with Cubk = 0.02% (CM3) andCu,; = 0.1 1% (CM13) the a,for the stressrelieved and as-tempered conditions aresimilar, and suggest no general trend. The AY,are lower for the stress relieved conditions forthe intermediate nickel (0.85%) low copperCu,, = 0.02% (CM5) steel containing highphosphorous (0.035%). This may indicatesome phosphorous removal from the matrixduring stress relief, but the magnitudes of thedifferences are small and probably within the

data scatter. Contrary to the general trend, Aa,are generally higher for the stress relievedconditions of the intermediate nickel (0.85%)steel with intermediate Cubk = 0.22% (CM 16).This may be a partial consequence of themechanisms associated with reductions in c,and dislocation recovery discussed previously.However there is no overall trend in the CM 16data, and this deviation from the norm is alsoprobably primarily associated with scatter.

The trends in the VSR Aca, data are certainlyconsistent with significant pre-precipitation inhigh copper steels. The behavior of the CMI Ialloys with 0.33% Cu suggests that theeffective maximum copper following typicalT,-t,, schedules is 0.3% or less. Further, theresults are qualitatively consistent with moreefficient pre-precipitation at very high coppercontents (e.g., CM1 2) and decreasing pre-precipitation with increasing nickel content(e.g., CM 18,19, 20).

Further quantification of these results wascarried out by using the modified NUREG-A, model to calculate the Cu, required toproduce the measured a, for the variousalloys and heat treatment conditions. Thebasis for the modified NUREG-Aa, model andCu, predictions are described in more detail inAppendix A. Briefly, however, as shown inSection 5, the NUREG-Ao, model predictionsare generally very consistent with the datafrom the intermediate flux T14 capsule. Thisconsistency was found using the NUREG CRPterm for welds for all of the steels irradiated inthis program, irrespective of their specificproduct form. Similar comparisons show thatthe NUREG-Aa, model overpredicts themeasured Acy, from the high flux T4 capsule.The difference between the T4 (high flux) andT14 (intermediate flux) data suggests a fluxeffect on AGr A strong and systematic effectof flux has also been observed in several otherIVAR data sets. Low flux accelerates the CRPevolutdon and shifts Aa, to lower fluence.

The discrepancy between the NUREG-Aaymodel predictions and T4 observations (or

52

In N .

CM3 a

Q MLrp_607 624

T (°C) - t(h)

-lN

641590

1u

75

50

25

UAT

n

bCM5........ ....... .. r

r

FL A AT

590 607 624T(°C) - t(h)

607 624T(°C) - t(h)

185t

160

135

CMII c

.. _. . ...............

I . -1 11 - I

' AT

641

I rnr

...... .............. ... ... ...............

CM12

L.... le i h ].. . .. .

590 607 624T(°C) - t(h)

r.

-'N AT641

590 607 624T(°C) - t(h)

641 590 607 624rC-t(h)

Figure 6-5 Variation of Aay with SR condition for a) CM3, b) CM5, c) CMI I, d) CM12, e)CM13, f) CM16

53

751

50b

25

A

dU.&W

1951

1701

145

120

590

100

641

I Afk

A' ' _ _i ' . . i - - ' .

1%I n%

-

*W

v

ui

i

590 607 624 641

225CM19 h

20 .

1 7

150

125 * R AT

590 607 624 641

T(Q-XQv

oilIatp

44

AT590 607 624 641

rQ-tm

Figure 6-5 (cont.). Variation of cTy with SR condition for g) CM18, h) CMI9, i) CM 20

54

between the T14 and T4 results) increases withincreasing alloy nickel and manganesecontent. The interactive effect of compositionand flux is consistent with defect trapping bythese elements. Trapping increases defectrecombination, hence, slows radiation-enhanced diffusion. Slower diffusion shifts theA;-curves to higher fluence. Details of theongoing investigations of the effects of fluxwill be presented in the future. For the presentpurposes, however, the NUREG-A,& model wasfurther modified to account for compositiondependent flux effects by including a nickeldependent flux-factor f,(Ni) = I(l+yNi, y -1.3) that decreases the effective fluence as Ot,= ft, in the CRP term of the NUREG-ca,model. This flux-dependent version ofNUREG-A&ay model fitted the high flux T4data was used to estimate Cu. for the high fluxVSR data.

Figures 6-6a to 6-6e show the Cu. estimatesfor the VSR study plotted against t Thecorresponding T. is indicated by the variousfilled symbols and Cub, by the unfilled circle.The Cu. in all the high copper (> 0.3%) alloysare substantially less than bulk levels. Forintermediate nickel (0.84% Ni) alloys, Cu.falls below 0.25% Cu. The Cu. renerallvdecreases with increasing t,,, and more weaklywith decreasing T, although individual datapoints scatter around these broad trends. Thelow nickel CM 18 alloy (0.02% Ni) shows arapid drop, approaching 0.2% Cu at 40 h forT,= 590'C. In contrast, the high nickel(1.68% Ni) CM20 decreases less, with Cu. -0.29 after the longest t at the lowest T,Figure 6-6f compares the Cu, trend in CM 19with those for low copper alloys with Cu, =0.22% (CM16) and 0.11% (CM 13). Forclarity no distinction is made between thevarious T,, in this case. The data for the lowcopper steels scatter around Cu.

Table 6-3 summarizes the Cu. estimates fromthe VSR study for the as-tempered conditionand the average values for the stress relievedconditions for 48 and 96h at 590°C and 24and 48 h at 6070. A similar analysis was

carried out for as-tempered and limited stressrelief data from the PB experiment. Theresults are shown in Figure 6-7 and thecorresponding Cu, estimates are given inTable 6-4.

Averaged results of the various estimates ofCu, for high copper, intermediate nickel steelsfollowing typical stress relief treatments fromabout 590 to 610°C are summarized in Table6-5. The overall average for the intermediatenickel steels (CMI 1, 19, LC and LJ) withnominal levels of Cu,: from 0.3 to 0.4% is Cu.,- 0.28%. In alloys with a high Cuk of 0.8%,the matrix copper is lower, with Cu. - 0.21%.This can be understood based on higher pre-precipitation nucleation and growth rates insteels that start with higher copper in solution.The matrix copper in the high nickel alloy(CM20) is larger with Cu, - 0.31%. The Cu., -0.27% in the low nickel steel (CM1 8), issimilar to that for the intermediate nickelalloys; however, this limited data may bebiased by the high estimate of Cu, from thePB capsule.

These estimates of Cu., based on Au,measurements are subject to considerableuncertainty, but reflect relative trends and the'practical' effects of stress relief. Theysupport the following general conclusions:

1. Typical heat treatments in the range of590-6101C for periods between 20 and 80h of intermediate nickel, high copper (Cu,5 0.3%) steels result in a reduction of Cu,to below 0.3% Cu, with even lower valuesfrequently observed.

2. General trends towards decreasing Cu. withdecreasing nickel, very bigh copper, lowerT. and longer t,, are observed. However, thedata do not allow precise quantification ofthese effects.

3. The best maximum copper fit value of0.25%Cu for intermediate nickel welds inthe PREDB is credible and consistent withthese result of this study. The observation

55

O..

0.1

0.1

0.;F0.

0.:

0.'

0.

5 a45 CMI I

40

35

30 2 -25' *

2'11CI ' '

' jO

AT

* 5900C

* 6070C* 6240C

o Bulk

25 50 75 100

th,(h)

O.50L 0.40 . CM18 c

0.40

0.35 a

0.30 * 0

0.25 A

0.20 0

0.15o 25 50 75 1(

AT* 590°C* 607 CA 6240Cv 641 C° BULK

0.

0.

0.ae 0.

3 0.0.0.

0.

U

5. 4 5 CM12 b

35'30

25t Y v

20 * *147 I A JO 25 50

th,(h)

75 100

0.5 d'

0.45 CMI9

0.4

0.35 0.3 3 A

0.25 * S

0.2

0.15o o% U o

tNt(h)

t a

tbg(h)

0.51

0.4

OX

eCM20

.4

.

0.21

0 25 50tt,(h)

75

AT

* 5900C

' 607 C

A 624 C' 641°C

° BULK

Ue

100 N o

tb(h)

Figure 6-6 Aoy-based NUREG model prediction of the variation in Cuin with SR timefor the VSR data for a) CMI 1, b) CM12, c) CMI 8, d) CM 19, e) CM20;

f) Comparison of high Cu CMI19 to two lower copper steels

56

s

0

A

-0

AT590 0C6070C

6240C

641°C

BULK

AT

* 5900C

* 607 CA 624°C

Y 641 Co BULK

0. I1 . .

)O b

r

0CM 19

CM20

A CM18

4: CM12

In~~~~~~~~~~~~~~~~~~

tht (h)

Figure 6-7 Acry-based NUREG model prediction of the variation in Cum with stress relief time for thePB data for CM12, CM18, CM19, CM20

Table 6-3. Estimated Cum for High Copper CM Alloys in VSR StudyAlloy CUbk AT-CUm 590°CCum 6070C-Cu

CM 1 0.33 0.29 0.26 0.25CM19 0.42 0.34 0.25 0.29CM12 0.86 0.38 0.21 0.21CM18 0.43 0.48 0.21 0.28CM20 0.43 0.34 0.30 0.31

Table 6-4. Estimated Cum for High Copper CM Alloys in the PB Study

Alloy Cubk AT-Cum 607'C/8h-Cum 6O7 0C40h-Cum 607'C-80h-Cum

CM12 0.86 0.37 0.32

CM18 0.43 0.47 - 0.35

CMIg19 0.42 0.36 0.33 0.33 0.29CM20 0.43 0.33 - 0.35

57

0.20

Table 6-5. Averaged Cum Following Heat Treatment at -590-610'C

Cubk/Ni T14 T4 PB PBSR VSR-1 VSR-2 AVG

CMI 1 0.26 0.28 0.25 0.28 0.27

CM19 0.27 0.29 0.31 0.27 0.28 0.28

LC 0.34 0.25 0.30

Li 0.30 0.26 0.25 0.27

CM12 0.21 0.32 0.22 0.23 0.24

LK 0.24 0.18 0.20 0.21

CM20 0.27 0.35 0.32 0.31

CM18 _ 0.22 0.35 0.27

that this maximum is lower in low nickel steelsand higher in high nickel steels is also broadlyconsistent with the present results. However,these statistical fit results do not preclude aslightly higher actual maximum copper or aheat-to-heat variability in this value dependingon many details of the alloy and its processinghistory.

6.3 Microanalytical Assessments ofCum

The Cu. estimates based on Aa, data have beencomplemented by limited microanalyticalstudies that are summarized below. Theseinclude field emission scanning transmissionmicroscopy (EGSTEM) carried out at AEAHarwell, electrical resistivity and Seebeckcoefficient measurements and small angleneutron scattering (SANS).

63.1 Field Emission Gun ScanningTransmission Electron MiScroscopy

Table 6-6 summarizes the FEGSTEM results onCu. for CM 19, CM 20 and CM 12. Most ofthese measurements were made after a so-called

UK quench and temper (Q&T) which differedsomewhat from the UCSB base Q&T. However,the alternative Q&T are not expected to make asubstantial difference to the Cu. results.

An intercomparison of these and other results isgiven below. However, overall they are veryconsistent with results of the Cu. assessmentbased on the Aa, data trends.

63.2 Electrical Resistivity

As discussed in Section 3, electrical resistivity, p,of metals and alloys can be precisely measured.While there are many contributions to resistivity,in dilute alloys the total is usually dominated bythe resistance of the pure solvent (e.g., Prj plusdissolved solutes (e.g., Cu, Ni, Mn,...). with lessercontributions from microstructural defects, traceimpurities and precipitates, p (Rossiter, 1987].In RPV steels, these 'other' factors typicallycontribute about 3 f-cm, out of a total of morethan 20 pacm. The p of simple dilute binaryalloys can be precisely related to the solutedistribution. Alloying and impurity elementslocated in large precipitates contribute little to pand to first order can be neglected [Rossiter,

58

Table 6-6. FEGSTEM Estimates of Cum for CM12, CMI9 and CM20

Alloy Tht(0C) Cum Cum

(As Quenched)t (thi short -h) tht = int. (h) tht long (h)

CM 19 550 0.35 *0.05CMI9 600 0.35 ±0.05 0.34 ±0.04 (8) 0.32±0.05 (40) 0.25±0.05 (80)

CMI9 630 0.35 ±0.05 0.29 ±0.05 (8) 0.30±0.03 (40) 0.24±0.05 (200)

CMI9 660 0.35 ±0.05 0.36 ±0.03 (4) 0.31±0.03 (40) _

CMI9* 0.42 :O.03 (8) 0.28±0.03 (40) 0.27±0.07 (80)

CM12 660 - 0.49 ±0.05 (4)

CM12 600 0.28±0.05 (40)

* Tempered at 660°C for different times; stress relieved at 600°Ct UK base was as quenched

1987]. The resistivity coefficients (ks) ofcommon elements (i) dissolved in iron areknown or can be established. For example, inthe case of copper, k,, - 3.5pG-cm/wt%[Mathon, 1995]. In the dilute solution range,the resistivity coefficients are approximatelyindependent of composition (p. = kjC,),although deviations from such linearity occurfor some elements like manganese (perhapsdue to clustering). Further, to first order, thenet contribution of different solutes in morecomplex dilute solutions is simply the linearsum of the individual contributions.

P - Pie +pm+ jk £kjC (6-5)

Consider an idealized case of a set of complexalloys that are identical except for the amountof one element x illustrated in Figure 6-8. Inthis example, the p of the alloy with C, = 0 isPo = Pi +P. = 2 2 p l2-cm and k = p-cml%x. Based on the assumptions listed abovethe p of the alloys would increase with thebulk solute content C,, up to the point whereprecipitation occurs at p. For equilibriumconditions the p would remain constant athigher C,1 (filled circles). The break point at p= 23.5pfl-cm defines the solubility limit of C^,= 0.3%. Thus alloys with C 2b> C,, andmeasured p., > p, (e.g., the open circle withCb = 0.6% and p.,= 24 pfl-cm) reflects non-equilibrium levels C.,, in solution. le C,b,

can be determined by the fit to the alloys withC,b less than the solubility limit (dashed line)as

C.1 = (p, - Po)/k = (24 - 22)/5 = 0.4%.(6-6)

Precipitation following additional stress reliefor irradiation would be reflected in p.2 (=23.75) < p,,, hence, lower dissolved Cx ,2(=0.35%).

Such idealized conditions cannot be met inpractice, except in the simplest cases.Complications include alloy-to-alloy variationsin solutes other than x, including the effects ofprecipitation during processing andconfounding variations due to otheruncontrolled contributions frommicrostructure. However, the approachillustrated in Figure 6-8 can be facilitated bycalibrating the k,. Plus a general alloy categoryterm, pj, accounting for all other factors for aparticular alloy class j, including contributionsfrom tnicrostructure and precipitates. Furthera term can be added to account for any secondorder nonlinearities in the compositiondependence of p, = k,C, +k1' C,2. ThusEquation 6-5 is modified as

p - pj + 1(k,C1 +k'C 2) (6-7)

59

Fitting Equation 6-7 requires a set of alloyswith a range of known compositions. The k,can be found only where there is a significantvariation in C,. Further, the qC must becorrected for the fraction that is not insolution, thus not contributing to p. For thepresent purposes this means that alloys with'high' copper cannot be used in the fit, sincethe corresponding Cu,,. are not known.However, since the corrections are generallysmall, other elements were considered to be insolution at bulk levels (e.g., Mn) or completelyprecipitated (e.g., C), hence lumped in with p,.Finally, it is assumed that the p accounts for allother factors in alloys in category j.

Equation 6-7 was fit to alloys in four classes:a) the VM series of simple ferritic alloys withvariations in Cu, Mn, C and N and heat treated

24.5

0~

23.5

22.5

I

21.50 0.2

to retain copper in solution; b) the LV alloyseries in its standard stress relief condition andone high copper alloy in the as-temperedcondition (LO); c) the CM alloys series in thestandard stress relief condition; and d) the CMalloys series in the as-tempered condition.The ki terms included Cu, Ni, Mn, Si and P.Only Mn benefited from a nonlinear k,. term.The effects of other compositional variables(C, N, Mo,..) were generally too small to beestablished and were lumped into the p, term.As noted above, all alloys were assumed tohave dissolved solute levels equal to the bulkchemistry with the exception of copper.Thisclearly is an approximation, particularly forthe manganese which is incorporated into M3Cphases in carbon containing alloys, as well asfor low solubility elements like phosphorous.

0.4 0.6 0.8

CXFigure 6-8 Idealized variation of resistivity with content C 1 of solute x.

60

a I * Ik

p = CX +22 - kx

0~~

wS

Cxe

p

The resistivity data trend themselves were used toguide the assumptions concerning the definitionof low copper alloys fit to Equation 6-7: VMCu, = Cub; LV and CM-standard stress reliefCu., up to 0.22 % copper; CM-as-tempered Cu,up to 0.33% copper.

The k1 and p, were used to normalize themeasured p to a common composition andalloy condition: Mn = 1.6%, Ni = 0.8%, Si =0.15% P = 0.005%, Ti = 0.0 and VM. Figure 6-9 shows the resulting variation in a normalizedresistivity, p., with copper. The overall standarderror in the fit is :t0.25 pfl-cm, or only about Ito 3% of the measured values. The individual fitparameters are given in Table 6-7. The k; arealso generally in agreement with publishedvalues. The low copper data used in the fittingare shown as the filled symbols. A least squares

14

13

0-,

Q

12

11

10

9 -- -

0.00 0.25 0.50 0.75

fit line to all this data gives a k, = 3.54 pfl-cm/% Cu in excellent agreement with results inthe literature [Mathon, 1995]. The standarderror for this fit to the p. data was ±0.2 pfl-cm.The open symbols are for the high copper alloysnot used in the fitting, since their Cu. wereunknown.

The high copper p. data for the CM alloys fallbelow the low copper fit line, indicating pre-precipitation. This is also the case for theintermediate nickel (0.85%), high copper(0.42%) LC alloy. However the other highcopper LV alloys with lower (LA and LB) andhigher (LD) nickel contents fall on or above thelow copper fit line. This suggests that in additionto this contribution to p1, nickel may alsoinfluence the microstructure term, pj.

* CM SSR < 0.3 Cu

* * VMa

a LV- SSR < 0.3 Cu

A CM-AT < 0.3 Cu119

0 CM-SSR > 0.3 Cu0/ O LV- SSR > 0.3 Cu

1.00

Cubk (%)

Figure 6-9 Variation of resistivity with copper content for a range of alloys

61

In order to further minimize possible effectsof heat-to-heat variability in estimating Cu.,analysis of the norrnalized resistivity data wasrestricted to the intermediate nickel alloys. Thelow copper data were fit both with (solid lines)and without (dashed lines) an imposed k, =3.5 fl-cm/% Cu. Figure 6-lOa shows theresults for the CM series with about 0.85%nickel in the standard stress relief condition.The estimated Cu, for alloys with Cu,, =0.33% (CM1) and 0.42% (CMI9) are Cu,=0.20±0.01 and

0.24±0.02 respectively. Note, somewhathigher values are found if the data point forCMIO with 0.02% copper is included in theanalysis. However, since this data point isinconsistent with the trend for other lowcopper alloys (CM3, CM13 and CM16), it wasnot used in the analysis. The correspondingCu, estimate for the CM12 alloy with Cub =0.86% copper is also unrealistically low (<0.1% Cu), perhaps also indicating an effect ofvery high copper on p. Since this value is wellbelow the solubility limit at 607°C, it is notshown. Figure 6-lOb shows the correspondingresult for the LV alloys. The p of alloy LCwith Cubk = 0.42% deviates from the lowercopper trends (LG, LH and LI), with anestimated Cu, = 0.3±0.01. Figure 6-lOcshows the results for the CM series in the as -tempered condition. In this case, as expected,both the CMl9 and CM12 show higherestimated values of Cu. - 0.32 and 0.48%Cu,compared to the standard stress reliefcondition. Unfortunately there is notsufficient data to carry out a similar analysison the high and low nickel CM series.

In summary the p-based Cu, estimates for thehigh copper steels are consistent withsignificant pre-precipitation of copper duringboth tempering and stress relief and stressrelief heat treatments. For the standard stressrelief condition Cu, - 0.2-0.3%. The lowestCu. was found for the alloy with the highestcopper (CM 12). This Cu. is quantitativelyunreliable, but the indicated trend is

qualitatively consistent with the previousanalysis.

6.3.3 Seebeck Coefricient

As described in Section 3, the Seebeckcoefficient (S, V/OC) can be measuredprecisely and is also sensitive to theconcentration of dissolved solutes in alloysand to a lesser extent microstructure [Pollock,1991; Miloudi et al, 1999, 2000]. The effectof solutes can be described by element-specific factors in forms roughly analogousto Equation 6-7. Most, but not all, soluteshave negative , hence, S usually decreaseswith increasing C,. Thus an analysis similar tothat used to estimate Cu, from the p data wascarried out based on measurements of S in theVM, CM and LV series alloys. However, thereare some possible differences between the Sand p behavior that require somemodifications of the approach. First, thedependence of S on C, is generally not wellestablished. Further, both theoreticalconsiderations and experimental observationssuggest that the S-dependence may be non-linear and sensitive to the total alloy solutecontent [Pollock, 1991]. Thus the effects of C,on S are represented by linear (), non-linear(K,' ) and a solute-total solute interactive(icj,C) terns as

S = S + 1i(K,C, + K,' C,2) xo,EC' (68)

Fitting Equation 6-8 to the VM, CM and LVseries database showed that good results couldbe obtained without the r.,C, terms, and thatnonlinear terms were (moderately) significantonly for nickel and copper. The fitting resultsare also given in Table 6-7. Note, not only dothe K,, have different values than p but theyalso vary in sign (e.g., K. > 0). The standarderror of the fit was about 0.22 pV/°C orroughly 2 to 3% of the measured S. Thenormalized S. versus Cu,, is shown in Figure 6-11. The normalization procedure and symboldesignation showing low copper (fitted -filled) versus high copper (not fitted-unfilled)are the same as those used in the p plots. The

62

0 0.1 0.2 0.3 0.4 0.5Cubk (%)

*12.0 a ILV

11.5-

211.0 10.5 _ b

K ~~~b

10.0 , . .0 0.1 0.2 0.3 0.4

CUbk (%)

14

13

12 o

11

CM-AT10 ,

0.00 0.25 0.50 0.75 1.00

Cubk (%)

Figure 6-10 Variation of resistivity with copper content for a) CM, b) LV and c) as-tempered CMalloys.

63

12.0

11.5

11.0a

10.5

10.0

Table 6-7 Least square fit calibration of Equations 6-7 and 6-8

Technique, Fe + 'Microstructure" Elements - ki (pW-cm/%i, k j(iV/0KI%i)Parameter r, (p-cm) S(iVPK)

LV. VM CM. CM. Si* Ti* P* Mn Mn2 Ni Ni' Cu Cu2

p, k 15.1 105 14.8 13.9 2.5 1.78 12.2 6.56 1.05 2A2 3.52

S

S, xij 8.0 13.7 10.3 10.1 3.56 0.49 16.1 0.24 1.62 0.31 5.94 u.5

1

11-

0

Ct

I

4* CM Cu < 0.3

2 £ * LV Cu < 0.3V 0* VM a Cu

0 0 LVCu>0,3O CMCu>0.3

8

60.00 0.25 0.50 0.75 1.00

Cubk(%)

Figure 6-11 Variation of Seebeck coefficient with copper content

64

normalized S decreases with increasing Cu,with a linear slope of -5.98 iVrC/%Cu. Thisis about 16% less than the value reported foriron-copper binary alloys reported in theliterature [Miloudi et. al, 2000] and mayreflect the interactions and non-linearitiesnoted above. The S. data for high copperalloys fall above this line, again indicating pre-precipitation.

The overall standaTd error to the simple lineartrend line of 0.2 pVPC indicates that a simplerexpression in the form

S= Sj +lC,,,X (6-9)

can be used to estimate Cu. for the highcopper steels. In order to minimize the effectsof alloy-specific confounding factors notaccounted for, Equation 6-9 was again fitted tothe various individual subsets of thenormalized (e.g., corrected for compositionand alloy category) intermediate (-0.85%)nickel CM and LV S. data. However, in thiscase no effort is made to fix c,,, at a nominalvalue.

The results are shown in Figure 6-12. Thedata for the model VM alloys are included butare not used in the fitting. Figure 6-12a showsthe results for the CM standard stress reliefcondition. The fitted ,,, is 5.61 pVrCI%Cu,reasonably close to the overall fit to the data.For the alloys with Cub, = 0.33% (CM 11),0.42% (CM19) and 0.86% (CM12) theestimates are Cu, = 0.25, 0.19 and 0.35%,respectively. Figure 6-12b shows thecorresponding results for the CM series in theas-tempered condition. In this case , = 5.57pVPCI%Cu is essentially the same as for thestandard stress relief case. As expected,however, the corresponding Cu., are generallyhigher for the as-tempered relative to thestandard stress relief condition with values ofCu., = 0.25, 0.26 and 0.42% respectively, forCMll, CMI9 and CM12. Figure 6-12c showsthe results for the LV series. The estimatedCu., for the intermediate nickel (0.86%) highcopper alloy (LC ) is 0.24% Cu.

In summary the S-based Cu. estimates for thehigh copper steels are also consistent withsignificant pre-precipitation of during bothtempering and stress relief heat treatments. Forthe standard stress relief condition Cu. forhigh copper alloys ranged from - 0.19-0.25%. The estimated Cum for the alloy withvery high copper (CM12) gave the highestCu. = 0.35, which is qualitatively inconsistentwith the other data trends and may be due toan effect of very high copper on S,.

6A Summary and Discussion ofthe Aay and Microanalytical BasedEstimates of Cu.

Table 6-8 summarizes the microanalyticalestimates of Cu. for intermediate nickel, highcopper steels for typical as-tempered and stressrelieved conditions. Note however, the specificheat treatments in these broad categories varyslightly. For example, most of the FEGSTEMCM data involve a so-called UK austenitize-temper treatment and air/furnace coolingfollowing isothermal stress relief. This differssomewhat from heat treatment schedules usedin this program. The p and S data are for theCM and LV alloys are in their specified as-tempered (CM) and standard stress relievedconditions (LV and CM). The Aa,/VSRentries are averages for both a range of typicalT. = 590-610°C and t = 24-96 h, as well asfor different Cu., assessment methods. Overallthere is reasonable agreement. These resultsare summarized in Figure 6-13.3

3Recent results have been obtained that provide furthersupport for the conclusion reached in this sectionregarding copper in solution following stess relief heattreatment for intermediatc nickel steels. These newresults include the following items. I) Changes in bothSeebeck coefficient (AS) and resistivity (Ap)measurements on CM, LV alloys and sevcral weldsfollowing irradiation show a similar pattern to the trendsfor the absolute values of these parameters (S and p) inthe unirradiated condition as shown in Figures 6-9 and 6-12. That is, the low copper steels follow a linear trendbut at higher copper levels the AS and Ap fall below thelinear trend line indicating pre-precipitation. For alloyswith Cubk > 0.30% a preliminary analysis indicates an

65

6.5 Small Angle Neutron ScatteringStudies from the PB Experiment

Figure 6-14 shows data from Small AngleNeutron Scattering studies on the effect of t.,from 0 to 80 h for T., = 607°C on the CRPfeatures for the high copper (0.42%)intermediate nickel (0.85%) alloy (CMI9)irradiated in the PB capsule [Wirth, 1998].Figure 6-14 shows both the total CRP volumefractions (f., filled circles) and thecorresponding estimates of the copper volumefraction (f 3, unfilled circles), based on themagnetic to nuclear scattering ratio. Figure 6-14 also shows the SANS volume fraction datafor the CM19 with t, = 24h at T, = 600°C,irradiated in the T4 capsule (open triangle).The x symbol is an adjustment toapproximately account for the lower fluenceof T4 (0.75x103 n/m2) versus the PB (x1023n/zn 2) capsule based on the corresponding ratio

of the NUREG CRP fluence functions (seeAppendix A). The f,, decreases withincreasing t,, to values of fc. - 0.25%,consistent with the corresponding evaluationsof Cu. described above. Clearly the effects oft, on Cu. in the unirradiated condition arereflected in the f. following irradiation.However, the f, cannot be used to directlyevaluate Cu., since precipitation is presumablynot complete at this fluence. However, therelative values are certainly meaningful andalso correlate well with the Acy changes.Further, since the as-tempered alloy has anominal f,. - Cut, - 0.42%, it is notcompletely unreasonable to assume that f,, -Cu.,. The open diamonds are adjustments toestimate the saturadon f based on dividingthe experimentally derived f values by theNUREG CRP fluence function for the PB andT4 capsules. These estimates of the saturationf,. also fall below 0.3% at long t,,

average Cum - 0.26 0.03%. 2) Recent AP data reportedby Miller show Cu. in the range of 0.19 o 0.27% for aweld with Cubk 0.3% depending on the stress relieftemperature and cooling rate. Note the effect of airversus slow cooling following a stress relief at 607°C for24h was also explored in this study. No systematicpattem was observed in the My for the high copper CMalloys (I, 12. 19 and 20) for these two cases. heaverage difference in y was approximately zero. Thuswhile slow cooling is expected to lead to lower Cu. theeffect does not appear to be large at least in this case.

66

Table 6-8. Microanalytical and A6y Based Estimates of Cu. for Typical As-tempered andstress-relieved conditions

Alloy/HT FEGSTEM p TEP Aay(av) Av.

CMI9/AT 0.36 0.32 0.26 0.38 0.34CMIIAT 0.33 0.25 0.33 0.30

CM12/AT 0.49 0.48 0.42 0.39 0.43

CM19SR 0.28 0.23 0.19 0.28 0.25

CMI I/SR 0.19 0.25 0.26 0.23

CM12/SR 0.28 0.34 0.24 0.23

LC/SR 0.28 0.30 0.24 0.27 0.27CM18/SR 0.27 0.27

CM20/SR 0.31 0.31

67

14 -w-1

12 X

2.

> 10

8

60.00 0.25 0.50 0.75 1.00

14 -- r

12

a 10

8

60.00 0.25

CUbk (%)

0.50 0.75

Cubk (%)

14

1212

2-

> 10

En

8I

6 0.25 . .Q.00 0.25 O.S0 0.75 1.00

Figure 6-12 Variation of Seebeck coefficient with copper content for a) stress-relieved CM,b) as-tempered CM and c) LV-series alloys.

68

1.00

I, LV

* VM

0.5 0.5

0.5

0.4

0.3

:f 0.2

0.1

0.0 -

0.4

0.3

:f 0.2u

0.1

0.0

1Z.4

Figure 6-13 Cum measurements from various techniques for a) CMI I, b) CMI9, c) LC

69

a CMIl O AT

O SSR0.4

0.3

f 0.2U

0.1

0.0:J

1Z

.

0.5 0.5

IT4-CM19, LC

0 0

x0

0

0

0 25 50

0

0

75

o Cu

Q Cu-sat

x LC-adj

* CRP

100

tsr Qb)

Figure 6-14 Effects of tr on CRP features as measured by SANS on CM19 from the PB capsule.

70

0.64

0.51

0.4

-

he

Wb.

$4

g

0.3

0.2 I

7 A PRE-PRECIPITATION MODEL FOR Cum

As noted above the data developed in thisstudy are not sufficiently accurate to derive adetailed time-temperature-precipitation C-curve model relating Cu. to the Cub,, T, t,, aswell as metallurgical factors such as nickel andbulk copper content. However, it is useful toevaluate general trends in the data to provideadditional guidance on Cu. limits within theframework of such a model. The most robustphysical consideration is that Cu. must remainat or above the equilibrium solubility limit ofcopper (Cue) in ferrite. The solubility limithas been examined with a number oftechniques and is given by [Kenway-Jacksonet al, 1993]

Cu,(wt%) = 120expl-5560/T (°K)1 (7- 1)

Figure 7-1 compares Cue to Cu. estimates forhigh copper CM alloys (CMI 1,12,18,19,20)from the VSR study based on the NUREGassessment method. The available data for 48and 96h at 590°C, 24 and 48 h at 607°C, 12and 24h at 624°C and 6 h at 641°C have beenaveraged in this plot (note data were notavailable for all materials for all theseconditions). The general trend is for Cu toincrease with T, at a small increment aboveCue. The divergence between Cu,, and Cu,increases with decreasing T, The high nickelCM20 data fall above the others, while theintermediate nickel and alloys with 0.33 and0.86% copper (CM1 1,12) copper fall near orslightly below Cue. The low and intermediatenickel alloys with Cub, - 0.42% lie in between.The dashed line, in the form of Equation 7-1,is a fit to the average (large plus symbols) ofthe high copper, intermediate nickel CMI Iand CM19 data and is given by

Cu, - I .lexp(-3282T,) (7-2)

Equation 7-2 represents a reasonable basis toestimate Cu, for 'typical' high copperintermediate nickel RPV steels as a function ofT, assuming reasonably long t,, The stressrelief time dependence of pre-precipitation

can be crudely modeled in terms of standardequations for diffusion-controlled growth ofprecipitates [Porter and Easterling, 1987] as

Cu,(t ,T.) =Cu.(AT)-[Cu,.(AT)-C,(T.)][ I -exp(k,.Y2 )]

(7-3)

Here Cu,(AT) is the Cu, in the as-tempered(AT) condition and k, is a transformation ratecoefficient that depends on the Cu,(AT), thecopper thermal diffusion coefficient and thenumber density of the pre-precipitates. Thus,k1, is also expected to depend on T,, andCuJ(AT). The transformation rate coefficientis physically complex but is crudely modeledas

k, = y,Cu,.(AT) Cubkexp(-E.J1) (7-4)

where ,, is a numerical constant, and the Cu,,term represents the effect of the bulk copperon the pre-precipitate number density (ornucleation rate) and E, is an activation energyterm that accounts for the combined effect ofT.r on copper diffusion and pre-precipitatenumber density.

Figure 7-2 compares the results for the highcopper intermediate nickel CM alloys(CI 1,12,19) from the VSR study, using theNUREG-Acry model to assess Cu,, topredictions using Equations. 7-1 through 7-4,with Y.= 1.33 x 10' and E, =20,000°K. Theresulting predicted Cu. values for CM 19 are ingood agreement with the VSR estimates, whilethe CMI 2 results are more scattered and theCMI I values are lower by an average of about0.05%. Figure 7-3 compares thecorresponding predictions of Cu, as afunction of t, for CM19. The effects of thevariation of k. with T,, are small and less thanthe uncertainties in the data. Thus it isreasonable to use a constant value of k, equalto that predicted for 5900C to model theaverage t,, behavior of a typical high copper,intermediate nickel steel as

71

Cu(t .T.)=Cum(AT)-[Cu.(AT)-Cu.(T,)][ 1-exp(-0.0 17t,3)]

(7-5)

Here Cu,(AT) = 0.35% for Cubk,> 0.35% andCum(AT) = Cub, for Cu,(T,) < Cub,< 0.35%.

At best Equation 7-5 can be used as a rule ofthumb for assessing the effects of stress reliefconditions on Cu. in low to intermediatenickel steels. The Cu, accounts for T, and theconstant k. crudely accounts for the t,.

0.35

0.30

Ug

JU

0.25

0.20

dependence. However, Equation 7-5 shouldnot be extrapolated below about 590°C,because of slower diffusion rates, or above640°C because reduced rates of pre-precipitatenucleation. Equation 7-5 is also not applicableto high nickel steels, where higher Cu. areanticipated.

Verification and further refinement of the Cu,.model will require additional data and moredetailed modeling.

* CM19

O CM18

* CMll

O CM20

+ Av. CM1l, 19

-a CUmcrsr)0.15 L-575

T (°C)

Figure 7-1 Comparison of Cu, to Cum for high copper CM alloys from VSR

72

600 625 650 675

0.20 0.25 0.30 0.35

Cum (pred., %)

* CM19

A CM12

* CMil

0.40

Figure 7-2 Comparison of Cum from VSR data to predictions of Equations 7-2 through 7-4.

-4

K AT

* 5900C

* 607°C

A 6240C

v 641°C

O BULK

d- 5900C

._-.- 6070C

..em--m. 6248 C

"m"llgn 641

Figure 7-3 Comparison of Cum for CM19 as a function of tsr.

73

0.40

0.35

UP

A=F

0.30

0.25

0.20

0.15 0.15

0.45

0.4

0.35

0.3

0.25

0.2MLh

tht (h)

.i

8 SUMMARY AND CONCLUSIONSThis study is part of an overall effort toprovide guidance and insight for supporting atechnical basis for proposed changes to RegGuide 1.99/Rev 2. The overall effort involvesdeveloping an independent embrittlementdatabase from controlled, single-variableexperiments. High-resolution experimentalmaps of the individual and interactive effectsof metallurgical and environmental variableson embrittlement are derived from irradiationand post-irradiation testing of very largeexperimental matrices. These experimentstake advantage of the relationship between ATand increases in yields stress (Aa,), which canbe measured using small tensile specimens.These experiments achieve precise control andcharacterization of the embrittlement variables.Irradiations are carried out in the IrradiationVariable Facility (IVAR) at the University ofMichigan Ford Research Reactor. The largeexperimental Aa, database under development,will ultimately be complemented by anextensive effort to characterize themicrostructural changes responsible for Acy,and AT. The collective results will be analyzedand used to develop quantitative, mechanism-based embrittlement models. These in turncan be used to support the development andjustification of statistical fits to the powerreactor embrittlement database (PREDB), suchas the Eason-Wright-Odette Model(NUREGICR-655 1) as a part of the technicalbasis for proposed changes to Reg Guide1.99/2.

This report has focused on a subset ofimportant questions that must be answered inestablishing this technical basis. The effortinvolved analyzing irradiation hardening datafrom three irradiation experiments (T4, T14and VSR) performed in the IVAR facility, andone irradiation experiment (PB) performed ina piggy back experiment.

Collectively, the T4, T14 and PB datapermitted the systematic investigation ofcompositional effects. The sigmoidaldependence of hardening on copper was seen,

as expected. The data also showed systematicincreases of hardening with nickel,phosporous, and manganese. The sensitivityto copper was enhanced by nickel and thesensitivity to phosphorous was decreased bycopper. The sensitivity to other chemicalelements - boron, carbon, nitrogen, trampelements - was small or negligible. Theobserved small sensitivity to molybdenum isconsistent with a superposition of irradiationhardening to pre-existing hardening fromstrong obstacles like Mo2C.

Data from these irradiations were compared topredictions of a Ao1 modification of aNUREG-AT correlation model. The overallagreement was quite remarkable. Thus theAo, database generated in this study provides apowerful and independent confirmation of thegeneral form of the NUREG model treatmentof copper, nickel and phosphorous and theirinteractions. All the major trends in both theNUREG model and in the IVAR database areconsistent with current understanding ofembrittlement mechanisms. Specifically, thedata validate the general two-component formof the NUREG-AT model comprised of acopper-independent (matrix feature, matrixfeatures) and copper-dependent (copper richprecipitate, CRP) terms, and corroborate thevery strong interaction between copper andnickel in the NUREG model CRP contributionto AT. The data also validate the inclusion ofphosphorous in the NUREG model, andsupport its approximate treatment in thematrix feature contribution to AT.

The VSR experiment permitted theinvestigation of the effect of systematicvariations in stress relief time and temperaturefollowing the final tempering of several sets ofA533B-type split melt alloys. These datademonstrated the systematic reduction ofmatrix copper, Cu., prior to irradiation by pre-precipitation. The pre-precipitation occurredto a greater extent with increasing stress relieftime and with decreasing stress relieftemperature. The irradiation hardening data

74

were complemented by FEGSTEM, resistivityand Seebeck coefficient measurements onunirradiated alloys subject to a range of stressrelief anneals. In addition to verifying theeffect of heat treatment on matrix copper, theemergence of resistivity and Seebeckcoefficient measurements as usefulnondestructive tools for assessingembrittlement potential were demonstrated.Together the data were used to develop asimple transformation model to estimate Cu,as a function of stress relief time andtemperature. In addition the data validate amaximum in Cu. of around 0.3% followingtempering and stress relief heat treatmentsfound in the NUREG model. Strong supportwas also found for even lower Cu, levels ofabout 0.25% in low-to-intermediate nickelsteels, as well as evidence for correspondinglevels in excess of 0.3% in high nickel steels.

unirradiated microstructure and properties,hence, also A;r, and AT.

4. Possible sources of product form variabilityand data scatter in the matrix features term,including an increase in A; withmanganese and nickel.

5. A possible interaction reducing the effectof phosphorus at higher copper.

These will be addressed in ongoing research inthe UCSB program.

The database and analysis provided in thisreport also provides additional insight intoseveral other issues, which are further fromclosure. Resolution of these issues could leadto signif-icant improvements in embrittlementforecasting. They include:

l. Possible sources of product form variabilityand data scatter in the CRP term. Theseinclude embrittlement contribu-tions fromelements not explicitly accounted for in theNUREG-DT model, like manganese(interacting with nickel and copper), andeffects of microstructural variations on thefluence dependence of Ay and AT.

2. An unanticipated effect of flux and flux-composition interactions on the fluencedependence of the CRP contribution to A,and AT.

3. Effects of the unirradiated constitutive andCharpy properties on: a) the Ac; -producedby a specified embrittlementmicrostructure; and b) the relationshipbetween Ay and AT. This work has alsoidentified new mechanisms that influencethe effects the heat treatment on the

75

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Odette, G. R. and G. E. Lucas, "RecentAdvances in Predicting Embrittlement ofReactor Pressure Vessel Steels," Proceeding ofthe 2"d International Symposium onEnvironmental Degradation in Nuclear Reactors- Water Reactors, J. T. A. Roberts, J. R. Weeks,G. J Theus, eds., American Nuclear Society, LaGrange Park, IL, 1986, p. 345.

Odette, G. R. and G. E. Lucas "The Effect ofHeat Treatment on radiation Harding ofPressure Vessel Steels," Proceeding of the 3rdInternational Symposium on EnvironnentalDegradation in Nuclear Reactors - WaterReactors, J. R. Weeks, G. J Theus, eds, TheMetallurgical Society, Warrendale, PA, 1988, p.95.

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79

Appendix A The NUREG Acy Model

A comprehensive effort to develop improvedembrittlement prediction models was reportedin NUREG/CR-6551 published in 1998 [Easonet al, 1998]. Statistical equations were leastsquares fit to the scrubbed Charpy V-notchtest energy-temperature data extracted frompower reactor embrittlement (surveillance)data base (PREDB). Embrittlement equationswere developed for both reductions in uppershelf energy and increases in the 41J transitiontemperature (AT). The latter were based on609 AT points in the PREDB. The NUREG-AT models contain two terms. The first isattributed to what is called in this report thematrix feature contribution, which occurs insteels independent of their copper (and nickel)content. The matrix features term depends onphosphorous, irradiation temperature (Ti) andfluence (t). The second term derives fromwhat is called the CRP contribution in thisreport. The NUREG CRP term depends oncopper, nickel, Ot and flux () or irradiationtime (t/0).

The most salient features of the NUREG ATmodels were that: a) the correlation equationswere based on an understanding of keyembrittlement mechanisms; b) selection fromamong a large number of statistically similarcalibrated correlation equations was based onboth mechanistic considerations andconsistency with independent sources of data,largely derived from UCSB test reactor studiespreceding the IVAR program, including datafrom the PB capsule; c) unless there was acombination of mechanistic and statisticalsignificance dictating otherwise, the correlationequations were kept as simple and with as fewdegrees of freedom as possible.

Improvements in the NUREG model havecontinued and currently focus on thefollowing questions and issues:

a. The treatment of phosphorous in the matrixfeature term.

b. The effective maximum copper content asinfluenced by variables such as product formand nickel.

c. Variability in the embrittlement modelcoefficients associated with product form,including subclasses representing a vendoreffect.

d. The effects of flux-time in the CRP termassociated with possible thermal diffusioncontributions to precipitation kinetics,primarily impacting very low flux serviceconditions characteristic of BWRs.

e. An additional possible non-conservative biasin AT at times in excess of about 1 O'h thatcannot be attributed to a particular mechanismor combination of other variables (althoughthis effect increases slighdy with increasingT.)

While not a major issue of contention, itremains important to evaluate the generalforms and variable dependence of both thematrix features and CRP, since some details ofthe correlation depend on all others. Thus amajor objective of this study has been tocompare the IVAR data trends with predictionsof the NUREG model.

Such comparisons require conversion of theAT predictions to corresponding values ofAo,. A strong empirical relation between ATand Ay has been observed in almost all caseswhere both types of data are available in caseswhere non-hardening temper embrittlement,associated with intergranular fracture does notplay a role [Odette et al, 1985]. However, theempirical hardening Charpy shift factor, Cc =ATIA,Y, vares in a typical range of about0.65±0.15 C/MPa. The AT-Ay relationshould also be consistent with themicromechanics of cleavage fracture.

80

A quantitative micromechanics model of C,has been developed [Odette et al, 1985]. Themodel includes treatment of both: a) Acyinduced shifts in the maximum temperature(T,) for cleavage preceding general yield(which occurs at a Charpy energy of aboutI OJ); and b) the layover in the Charpy energy-temperature curve in the transition that is berelated to the decrease in the upper shelfenergy (AUSE) that can also be relatedempirically to Aa,. As a consequence of thetemperature-dependence of a and thecontribution of the USE drop to the 41 J AT,Cc depends on the unirradiated Charpyproperties (T,U and USE,) and Acy. Thus thismodel explains part of the observed variabilityof C.

The NUREG-AT model does not explicitlyaccount for the variations in Cc due todifferences in unirradiated T,. and USE".However, it does implicitly account for AcrThus the average of values in the T, and USE.in the NUREG PREDB were used in the modelto determine an average relation betweenAT(0C) and A;, (MPa). The results can be fitto a convenient analytical form

C.(AT) = AT/AY (A-l)

WhereA; - 6.59x10 4 T3-4.67xl o *AT2+1 .78*AT+3.432

Figure A- I shows that Cc increasessignificantly with increasing AT (and A,).However, while such tends have been observed,the quantitative relationship has not been fullyverified by experiment, particularly at highA;. and C, > 0.8. Further, within data scatteran average value of C, = 0.7 is a reasonableapproximation to relate to A; - AT/C: Thusthree options were used to convert theNUREG-AT to AG,r including: a) Equation A-1; b) Equation A-I up to a maximum C.=0.8; c) an average constant Cv= 0.7.

The NUREG-AT model is given by

AT = AT,r +ATp (A-2a)

where

AT 1, = Aexp{ 1.9lx104(Ti.+460)1(1 +57.7P)¢t' 0 " '*'"

AT., = B(1l+2.56Ni'35')h(Cu)g(t)

and

h = 0, for Cu _ 0.072%,

h = (Cu - 0.072)f'for 0.072 < Cu <0.3%

b = 0.367 for Cu2 0.3%

(A-2b)

(A-2c)

g(ot)=0.5 +0.5tanh[(ogt-l8.29)/0.6](A-2d)

The T,' is in °F and the g(ot) ignores a smallcontribution from irradiation time that is notpertinent to assessing the test reactor data inthis report. The corresponding bA weredetermined as Aa,= AT K,, based on one ofthe three options listed above.

The NUREG-Aa, model was used in analyzingthe IVAR data. In all cases the A and Bparameters for welds from the NUREG modelwere used since this choice provided the bestresults and welds cover the widest range ofcopper and nickel in the PREDB. The analysisinvolved:

1. Adjusting Acty for the LH and LI (- 0.74%)alloys to account for small differences innickel compared to the high copper LV andCM alloys ( - 0.83:0.03%). This was done byadding the NUREG predictions of AaANi forLV or CM) - a,(Ni = 0.74%) to theexperimental AC,1 using the set of otherpertinent variables. This small adjustment, oforder 10-15 MPa, was based on the basicNUREG model and use of option b above forC.

2. Comparison of the Ay predicted by theNUREG model for the specified alloy

81

chemistry, irradiation temperature and fluenceto the corresponding experimental data fromthe T14 capsule. Flux was not explicitlyconsidered in this comparison, and option babove for C, provided the best results.

3. Comparing the a, predictions of theNUREG model (the matrix feature term) to thecorresponding data for low copper CM steelsfrom a number of IVAR capsules for low(0.005%) and high (0.040%) nominalphosphorous contents. This used the basemodel and option b for C,.

4. Evaluating Cu, from the ha, data from theVSR study. The VSR data are from a high fluxcapsule. Although not the focus of this report,other IVAR data show that higher flux shiftsthe Aa:(Ot) CRP contribution for a particularalloy to higher fluence. Thus the NUREGmodel was modified to account for the effectof flux. The approach was based on analysisof the data from the high flux T4 capsule. Anumber of modified NUREG models weretried to find a plausible treatment of flux thatprovided a good fit to these data. It was foundthat a very good fit could be achieved byusing option c for Cc above, and a flux factor(f, 5 1) to reduce the actual fluence to aneffective fluence at high flux. Further, it wasfound that fitting required a f4 that decreasedwith increasing alloy nickel content. Thisbehavior is consistent with higher rates ofinterstidal recombination with vacanciestrapped on nickel solutes. The fit provided byf,= 1/(1+1.3Ni) is shown as the filled circles inFigure A-2 comparing the A,predicted bythe modified NUREG model with the datafrom the T4 capsule. The unfilled circles arethe corresponding results for f = 1. The needto account for nickel is illustrated in Figure A-3. Here the differences between the predictedand measured a, are plotted against nickelfor the T4 capsule steels with more than0.072% copper. Data for the low manganeseand highest copper alloys and one weld (67W)with a large inexplicable discrepancy are notincluded in this plot, since they are notrepresentative of the other IVAR or the

PREDB data trends (note the low manganeseresult is consistent with the lower sensitivity offorgings in the PREDB). The discrepancybetween the Acy, predictions of a fluxindependent NUREG model and experimentincreases with increasing nickel. This trenddemonstrates the need for a nickel-dependentf in the modified NUREG model. However, itshould be emphasized that the f,(Ni)modification does not represent a quantitativeflux model. Rather, it represents an attempt tocalibrate the modified NUREG model toestimate relative values of Cu. using data fromthe VSR study.

Application of the modified NUREG-model isstraightforward. The specific nickel andphosphorous contents along with the VSRirradiation temperature and fluence are used tocompute Aci, using the modified NUREGmodel as a function of copper. The copperthat gives the predicted Acy equal to themeasured value is taken as Cu,.

82

IWU

0

U

1.0

0.9

0.8

0.7

0.6

0.5

0.40 50 100 150 200 250

AT (°C)

Figure A-I Variation of Cc with AT. The dashed line shows the average.

400 . I I

T4-alI data

300 f = 1(1+1.3Ni)

s 0 ° f¢=

Z 200

.0t o

00 100 200 300 400

AcFy (pred., MPa)

Figure A-2 Comparison measured ,ay with values predicted from NUREG model for T4.

83

6

aft-

100

75/

X 50 -/

d 25 -0

e o

-25i. 0.0 0.5 1.0 1.5 2.0

Ni (%)

Figure A-3 Variation of the difference between predicted and measured Aay with Ni.

84

APPENDIX B TENSILE DATA FOR T4, T14, VSR AND PBTable T4. Data for Capsule T4

Alloy

CM3CMIOCMIlCM13CM15CM16CM17CM18CMl9CM20CM21CM22 (series a)CM22 (series b)

LALBLCLDLGLHLiLiLKLO

Baseline kradiated Baseline IrdiatedCry *aGy Ca, :toy aC, tACF, uts tUts Uts tuts auts ±LAuts

MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa428429438424433434451433450464398406446

469483491501493507512530551527

12 43311 4526 587

11 4645 478

14 5589 6508 4924 602

11 7168 5057 5456 575

6 5499 5634 6363 6717 5264 5446 617

12 6718 6639 712

ORNL73 weld 507 13 639EPRI C weld 536 5 656B.W. weld 62 526 8 620B.W. weld 63 497 7 632B.W. weld 65 473 7 573B.W. wld 67 514 16 581ORNL A302b 557 18 580ORNL HSST02 plate 473 4 570JRQ plate 484 8 543

14 5 18 53110 23 15 52012 149 13 5274 40 12 5127 45 9 5169 124 17 5233 199 10 5487 59 11 5217 152 8 5457 252 13 5619 107 12 4646 139 9 482

129 6 515

13 80 15 58311 80 14 5903 145 5 6095 170 6 6336 33 9 6091 37 4 616

11 105 12 6281 141 12 6413 112 8 6442 185 9 638

6 132 14 6103 120 6 6264 94 9 6270 135 7 5988 100 11 5756 67 17 6064 23 18 690

10 97 11 6191 59 8 601

16 523 12 -8 2015 537 13 17 2011 658 10 131 1517 540 8 28 198 549 13 33 16

16 635 8 112 1814 718 8 170 1615 564 5 43 1611 666 10 121 1519 784 11 223 2211 550 7 86 13

6 598 3 116 77 622 107 7

6 656 10 73 127 667 4 77 84 745 6 136 73 791 1 0 36 637 6 28 92 650 1 34 27 719 11 91 134 758 1 117 46 746 5 102 88 808 1 170 8

12 726 6 116 138 731 5 105 98 700 1 73 85 716 3 118 66 661 6 86 8

15 663 4 57 1519 714 0 24 194 700 4 81 6

10 657 1 55 10

u = undereniined

85

Data for Capsule T14

Baseline lradiaed Baseline hmdiateda ±0 Ci, ±O AO ±Aa7 uts ±uts uts ±uts Auts ±AUtSNa MI MPa Miia Ma MPa MPa MPa MPa MPa MPa MPa419 8 416436 9 472428 12 434458 13 490394 21 453453 9 476457 17 502400 6 393416 5 427429 11 455438 6 610496 9 634421 2 483429 14 492434 13 476434 13 582451 9 676433 8 496450 4 621464 11 736398 8 513406 7 562446 6 591404 3 416463 13 481443 6 462444 6 456445 5 447438 14 435448 10 634265 7 343481 9 619444 6 442

469 6 549483 9 577491 4 660501 3 701493 7 528507 4 553512 10 619530 12 684551 8 680527 9 709

8 -3 12 4974 36 10 527

10 6 16 5315 32 14 5599 62 24 488

21 23 22 55216 45 24 56611 -8 12 4780 11 5 4991 26 11 5204 172 7 5276 138 11 590

10 62 10 50711 63 18 5266 42 14 5234 148 14 5235 225 10 5483 63 9 5211 171 4 5456 272 12 5616 113 10 4645 156 9 482u 145 6 5156 12 7 4791 18 13 5992 19 6 532

19 12 20 529u 2 5 537u -3 14 5291 186 10 5382 78 7 3795 138 10 5791 -3 6 514

8 80 10 5838 94 12 5904 169 6 6091 200 3 6333 35 7 6091 46 4 6168 107 13 6284 154 13 6418 129 11 6441 182 9 638

9 48015 55216 57513 57518 566

8 55920 6069 472

15 50515 53811 71812 71117 53415 58516 54916 65114 73915 56811 69019 79911 564

6 6177 6494 486

23 61113 5459 5378 529

18 5238 696

12 43411 6988 512

6 6577 6774 7643 8106 6362 6586 7214 7736 7638 811

17 -171 25

13 -103 168 0

27 712 40i -710 64 185 1528 121

27 2713 599 266 1284 1917 475 1458 2387 975 135u 1345 78 12

25 1318 8

u -8u -120 1584 556 1198 1

6 747 872 1552 1772 271 425 934 132

12 1191 173

1915211320281214181512151720181715161221138762528208

188

13138

910536286

138

86

Alloy

CMICM2CM3CM4CM5CM6CM7CM8CM9CM1OCM]ICM12CM13CMI4CM15CM16CM17CMI8CMl9CM20CM21CM22(setl)CM22(set2)CM 23CM24CM25CM26CM27(setl)CM27(set2)CM28CM29CM30CM31

LALBLCLDLGLHULiLKLO

T14 - cont'd

Baseline lndiated Baseline hadiatedcry :t, , Gy Au, tAy UtS ±uts utS *uts tuts *AutsMPa MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa MPa

ORNL 73 WeldEPRI C weldB.W. A weldB.W. B weldB.W. C weldB.W. weld 62B.W. weld 63B.W. weld 65B.W. weld 67Rolls Royce Weld WVRolls Royce Weld WGRolls Royce Weld WPORNL Midland WeldORNL A302bORNL HSST02 plateB.W. A508 plate

507 13 654537 6 674514 15 620510 11 625470 6 509526 8 624497 7 642473 7 568514 16 593462 8 761422 6 583472 3 514522 8 641557 18 599473 4 586418 8 447

7 1472 1371 1066 1157 392 984 1457 95

21 792 299

12 1613 424 1196 42

10 1135 29

15 610 12 7376 631 6 749

15 610 10 70212 611 6 7119 572 6 6038 627 8 7058 598 5 722

10 575 6 63126 606 .15 675

8 559 8 82914 533 8 6754 571 3 6089 623 9 723

19 690 19 72311 619 4 7149 573 9 591

u = underternined

87

5 1272 1181 925 1001 314 781 1244 56

15 696 270

13 1422 375 998 338 953 18

136

1086957

2110153

102199

Data for Capsule PB

Baseline hIadiated Baseline 1riateday :osy 0, : ay ±A* Ba uts ±Uts uts ±uts Auts ±Auts

MPa MPa MPa MPa MPa MPa MPa MP MPa MPa MPa MPa

CM I-as temperedCM2-as temperedCM3-as temperedCM4-as temperedCM5-as temperedCM6-as temperedCM7-as temperedCM8-as temperedCM9-as temperedCM1O-as temperedCMI 1-as temperedCM12-as temperedCM 13-as temperedCM 14-as temperedCM15-as temperedCM16-as temperedCMI 7-as temperedCMI8-as temperedCM19-as temperedCM20-as temperedCM21-as temperedCM22-as temperedCM23-as temperedCM24-as temperedCM25-as temperedCM26-as temperedCM27-as temperedCM28-as temperedCM29-as temperedCM30-as temperedCM31-as tempered

alternate heat treatmentsCM5* aged 480°100hracCM8* 400°C s.q.(not 4500)CM12* s.r. 600° Shr/ ac.CM18* s.r 600° 40hr/ ac.CMI 9* s.r. 600° 8hr/ ac.CMI 9* s.r. 6000 40hr/ ac.CMl9* s.r. 600° 80hrl a.c.CM19* 500°C s.q.(not 4500)CM20* sr. 600° 40hr/ a.c.CM20*500°C s.q.(not 450)CM23* 400°C s.q.(not 450°)CM26* aged 480°lOOhr/ac.

451477447533493541486434450460480505474476477477497464490478454480412496475471488498315498472

519422499437476463464495467507425490

8 4648 5407 4818 60027 57314 59016 58714 4501 4626 4994 6675 7143 51518 5618 5304 6138 7264 56616 69811 7696 5634 65113 41012 5255 51316 49817 49912 7017 39418 63611 505

17 53933 4398 68220 5226 66712 65321 63712 6945 77325 82312 4483 487

a2 13 8 521 4 538 16 63 10 558 11 632 0

20 34 21 535 8 569 264 67 9 635 15 686 48 80 28 585 32 671 104 49 15 632 19 681 29 101 18 589 9 693 6

21 16 25 521 15 532 189 12 9 530 6 536 78 40 10 545 6 582 42 187 5 580 4 749 6

32 208 14 589 4 802 105 41 6 560 5 591 58 86 20 566 28 653 84 52 9 546 10 601 21 136 4 561 5 685 15 228 10 591 7 808 15 102 6 542 4 638 1110 205 19 590 24 787 156 291 12 588 10 866 13 109 7 516 6 620 11 171 4 543 7 704 13 -2 13 492 12 490 6u 29 u 619 23 664 u5 38 7 563 19 594 84 27 17 572 21 585 534 11 38 571 19 581 2816 203 20 587 18 776 1925 79 26 430 5 486 2620 138 27 591 28 696 1010 33 15 556 15 586 15

35 20 39 639 20 640 4615 18 36 504 18 510 155 183 9 591 17 749 103 85 20 518 6 583 115 191 16 572 10 741 64 190 13 554 25 727 05 173 22 566 25 713 106 200 14 601 11 775 119 306 11 550 4 842 163 316 25 609 33 908 11

37 23 39 503 14 522 3526 -3 26 592 9 581 42

1775355186491031263716921331875412521796197277104161-245321210

1895610530

I6

1586516917314717429229919

-12

41127

15.533.519.110.8249771172910571129106714u

21223426273021

* 50232061225271617353843

88

Alloy

Baselne Eradiaed°Y ±C01 CaY tGy AcOy ACoy

MPa MPa MPa MPa MPa MPa462484513493498497527537497

154158152216220174175176179226154207214240196169218223181209

10 534 0 716 569 5 862 729 0 216

10 529 29 368 558 2 598 623 4 125

12 683 3 15613 667 u 13010 719 3 223

15 196 20 4217 260 17 1022 222 43 706 522 3 3063 428 3 2087 348 6 175

12 393 4 21815 351 2 1758 397 17 2185 259 4 33

11 178 19 247 356 5 149

17 430 4 21710 464 11 22514 443 14 2473 321 1 1526 536 8 3187 443 3 219

13 220 1 397 245 1 36

Baselne Iffadiaduts tuts uts tuts Auts t-AutsMPa MPa MPa MPa MPa MPa

579 8 643 1 64 8600 4 689 4 90 6649 7 840 0 191 7613 16 654 19 41 25620 13 665 0 45 13615 5 723 4 108 6641 14 775 2 134 14644 8 762 u 118 8613 10 827 3 214 11

25 217 13 230 26 1424 215 12 325 16 11043 204 16 257 38 54

7 310 7 579 2 2684 322 5 489 1 1679 257 10 390 1 134

13 252 14 444 4 19215 261 22 412 1 15118 257 10 447 10 1906 289 8 299 4 10

22 269 2 283 9 149 277 19 400 1 123

18 312 9 493 1 18115 332 11 523 3 19220 327 21 515 7 187

3 272 5 376 7 10410 304 5 582 14 278

8 343 14 520 2 17613 240 7 258 3 187 271 9 287 9 16

292041

75

1015221499

199

12229

15148

13

U = undeternined

89

PB cont'd

Alloy

LALBLDLGLHLILiLKLO

VAVBVcVDVEVGVHVIVJVKVLVMVNVoVPVRVsVTWVW

Data for VSR CapsuleBaseline lradiated

Alloy SR

CM3 5900C/24hCM3 590°C/48hCM3 590°C/96hCM3 607°C/12hCM3 607°C124hCM3 607°C/48hCM3 607°C/96hCM3 607°C/24h-air coolCM3 6240C/12hCM3 624°C/24hCM3 624°C/48hCM3 641°C16hCM3 641°C/12hCM3 641°C/24hCM3 AT

590°C24h590°C148h590°C/96h607°C/12h607°C/24h607°C/48h607°C/96h607°C124h-air cool624°C/12h624°C/24h624°C148h641°C/6h641 C/12h641 °C/24h

CMII 590 0C/24hCMII 590°C/48hCMI I 590°C/96hCMI I 607°C/12hCMI I 6070C/24hCMI I 607°C/48hCMI I 607°C196hCMI I 607°C/24h-air coolCMI I 624°C112hCMII 624°C124hCMI I 624°C/48hCMI I 641 C/6hCMI I 641C112hCM I 641°C124hCMIl AT

Baseline hmiateda, ±ay cy C,1 Aay ±Aq, uts ±uts uts ±uts Auts ±Auts

MPa MPa MPa MPa MPa MP MP MPa MPa MPa MPa MPa

447414369431428410302448421417397409392306479

359337267388No

371257411375365364363355293

4 45723 4457 394

21 45612 45913 43816 2851 455

26 4494 4401 4133 4321 410u 3347 507

47 42635 410

5 358u 440

da5 4198 320u 447u 4308 426

31 4126 407u 412

21 360

471 14 612450 6 600421 23 591466 21 633446 15 582445 18 596365 34 573486 1 588452 12 612453 2 582425 0 571432 2 600432 9 590393 0 585490 5 636

1 1021 31

8 2515 250 315 27u -173 186 284 238 164 234 18

30 281 28

4 53731 49511 45025 52312 53114 49716 4223 520

27 5136 5089 4915 5064 488

30 4347 566

33 67 57 46829 73 46 44854 92 54 41022 52 22 494

1 49 5 47311 63 14 3998 36 8 494

23 55 23 48217 61 19 47112 48 33 4572 44 6 480

10 57 10 46541 68 46 428

6 1417 1515 1704 1678 136

13 1516 208

16 10217 16111 1308 146

24 16925 1582 1928 146

15 56610 53824 49921 57017 53922 54534 46316 57421 55712 5578 523

24 53426 536

2 5009 577

8 54024 5174 467

21 53916 54822 5246 4116 527

25 5387 5290 5014 5231 500u 4434 596

44 52224 5054 468u 541

8 50713 444u 541u 5269 529u 507

11 512u 520

14 478

23 6899 677

27 65620 71422 65023 67319 6351 654

15 6931 6590 6523 686

10 6740 670

19 722

6299

2106u

9106684

172

32216161727

-111925211018129

1038102916

236

112796

9417

33 54 5524 57 3432 58 3225 47 25

7 34 114 45 136 47 6

12 44 1212 58 155 50 51 32 11

11 55 1133 50 35

8 1234 1394 1573 1446 Ill

16 1284 173

16 8018 13611 10311 12928 15224 1380 170

13 145

241027202328201623111128260

23

90

CM5CM5CM5CMSCM5CM5CM5CMSCMSCMSCM5

CM5CM5CM5

I

VSR - cont'd

Alloy SR

CM12 590°C/24hCM12 590°C/48hCM12 590°C/96hCM12 607°C112hCM12 607°C124hCM12 607°C148hCM12 607°C/96hCM12 607°C/24h-air coolCM12 624°C112hCM12 624°C124hCM12 624°C148hCM12 641°C/6hCM12 641 C/I2hCM12 641°C/24hCM12 AT

CM13 590°C/24hCM13 590°C/48hCM13 5900C196hCM13 607°C/12hCM13 607°C/24hCM13 607°C148hCM13 6O7°C196hCM13 624°C/l2hCM13 624°C124hCM13 624°C148hCM13 641°C16hCM13 641°C112hCM13 641°C124hCM13 AT

CM16 590°C/24hrsCM16 590°C148hrsCM16 590°C/96hrsCM16 607°C/12hrsCM16 6070 C/24hrsCM16 607°C148hrsCM16 607°C/96hrs

Baseline riadiaedCG toy cy ±UY

MPa MPa MPa MPa

494486482488499475461495487479464478466452515

438416407439419368327408294192304197190479

469438450452450448374

CM16 607°CT24hrs-air cool 459CM16 624°C112hrs 427CM16 624°C/24hrs 418CM16 624°C/48hrs 410CM16 641°C/6hrs 451CM16 641°C112hrs 395CM16 641°C/24hrs 354CM16 AT 503

u 621u 617u 600u 633u 6191 607u 594

27 650u 624u 613u 6101 6274 6122 6104 708

23 48224 464

8 44921 473

5 47517 4240 423u 456u 3801 293

62 4101 2932 286

13 537

15 6006 5741 554

21 57814 58411 55720 53316 58112 5664 562

17 5544 561

24 5641 5156 602

Baseline ImdialedAa, ±bao uts ±uts uts tuts Auts ±A^utsMPa MPa MPa MPa MPa MPa MPa MPa

4 1275 1313 1188 1451 120

14 1338 133u 1559 1371 1342 1461 149

13 1466 159u 193

4 5805 5773 5638 5711 589

14 5628 533

27 5729 5831 5572 5461 566

13 5546 5314 601

23 45 32 52216 48 29 4934 42 9 4861 34 21 5306 56 8 504

18 56 25 45213 96 13 43011 48 11 '496u 86 u 4124 101 4 348

31 106 70 4174 96 4 3555 96 5 3538 52 15 566

1 1315 1366 1041 126

17 1344 1098 159

11 1222 1393 1441 1436 1101 1684 1623 99

15 5698 5257 534

21 54422 54612 54222 46519 54012 5215 510

17 5078 550

24 4974 4667 588

u 688 7u 680 0u 660 10u 707 3u 695 28 679u 644

33 719u 685u 675u 6746 7052 6831 672

10 795

30 55930 53011 51331 5484 561

11 4930 495u 530u 4670 397

29 4952 4003 405

25 631

9 6799 6514 620

21 65823 66612 63311 5993 653

15 6448 641

16 6360 640

17 6463 5973 691

10810397

136106

13 1176 111u 1478 1021 118

11 1281 1399 1291 142u 194

70

1032

166

3381

11692

10

30 37 4316 37 347 28 136 18 328 57 9

15 41 1911 65 1120 34 20

u 55 u

5 49 533 78 442 45 36 52 64 62 25

1 11013 1266 86

11 11413 1206 916 134

19 11312 12311 1314 1286 906 1497 131

13 103

9157

24261312191914176

188

13

91

VSR - cont'd

Baselire 1zmae Baseline ITadiated(Ty toy ay :toy a, tAo uts ±uts uts tuts Auts t:uts

Alloy SR MPa MPa MP MPa MPa MPa M a MPa MPa MPa MPa MPaCMI8 5900C/24hrs 451 16 523 2 72 16 539 12 601 4 62 12CM18 590°C/48hrs 446 10 505 6 58 12 537 4 574 6 37 7CM18 590°C/96hrs 418 13 480 8 62 16 497 19 545 20 48 27CM18 607°lC2hrs 451 9 522 9 71 13 541 10 593 8 52 13CM18 6070 C/24hrs 433 8 510 9 77 12 521 15 587 4 66 15CM18 607°C148hrs 435 6 499 3 64 7 521 3 572 1 51 3CM18 6070 C/96hrs 394 7 460 2 66 7 471 4 522 1 51 4CM18 607°C/24hrs-aircool 452 4 532 6 81 7 529 1 598 7 69 7CM18 624°C112hrs 439 3 506 13 67 13 528 4 579 11 51 12CM18 6240 C/24hrs 431 15 498 0 67 15 517 6 576 3 59 6CM18 624°C/48hrs 413 6 486 6 73 8 502 7 564 9 62 12CM18 641C/6hs 421 2 498 4 77 4 519 6 581 3 62 7CM18 641°C112hrs 420 5 490 8 70 9 505 9 564 8 59 12CM18 641°C/24hrs 402 5 481 1 79 5 491 2 554 3 63 4CM18 AT 478 5 579 5 101 7 569 10 659 6 90 12

CM19 590°C/24h 449 12 626 4 177 13 543 19 705 2 162 19CM19 590°C148h 448 6 595 1 147 6 545 10 663 10 118 14CM19 590°C/96h 440 12 582 2 142 12 528 25 637 1 109 25CMI9 607°C12h 446 8 636 8 190 11 541 17 718 11 176 20CM19 607°C24h 447 5 615 11 168 12 538 11 690 12 152 16CMI9 607°C148h 435 12 597 3 162 12 528 21 679 2 150 21CM19 6070C/96h 404 17 582 9 178 20 483 17 644 8 161 19CMI9 607°C/24h-air cool 459 16 612 4 153 17 533 21 681 14 148 25CM19 624°C/12h 437 14 618 11 181 18 536 22 697 18 161 28CM9 624°C24h 430 5 601 5 170 7 531 9 681 6 149 11CM9 624°C148h 419 23 588 14 169 27 516 28 669 16 152 32CM19 641°C16h 432 1 609 1 177 1 542 11 692 2 150 11CM19 641°C112h 420 16 595 6 190 17 528 16 671 8 160 18CMI9 641°C24h 369 3 575 4 206 5 482 3 656 4 174 5CM19 AT 495 4 671 3 176 5 568 19 756 3 188 19

92

I

VSR - cont'd

Baseline Indiated

Alloy SR

CM20 590°C124hCM20 590°C/48hCM20 590OC/96hCM2O 607°C1l2hCM20 607°C/24hCM20 607°C/48hCM20 607°C/96hCM20 607°C/24h-air coolCM20 624°C/12hCM20 624°C124hCM20 624°CJ48hCM20 641°C/6hCM20 641°C/12hCM20 641°C/24hCM20 AT

gy ±, ;y , ±0 y , Ac, utsMPa MPa MPa MPa MPa MPa MPa

473461459453468466449409450449406439417384490

15 7228 722

15 7043 722

14 72211 71911 71215 6967 726

11 72120 71111 72624 71010 7072 759

10 2498 2611 2454 2694 2542 253

12 2636 2876 2760 2729 3051 2871 2934 3231 269

Baseline hrAdiated

18 56612 55615 5475 530

14 56111 56317 54316 49610 55311 55222 51311 54624 52811 5102 574

±uts uts tuts Auts tAUtsMPa MPa MPa MPa MPa

24 7899 792

22 7571 780

19 79413 78710 77912 75423 79918 79018 77419 80421 78012 7761 837

9 22311 2361 2101 2508 2334 224

23 2364 2588 2460 2385 261

13 25812 2523 2662 263

2614222

201325122418192324122

93

NRC FORM 13! US. NUCLEAR REGULATORY COMMISSION 1. REPORT NUMBER(2-M (Aned by NRC, Add VaL. Supp., Rev..

32oM 2. BIBUOGRAPHIC DATA SHEET dMumNumb%VSfly

2. T_LE AN SUBTrTLE NUREG/CR-6778

The Effects of Composition and Heat Treatment on 3. DATE REPORT PUUSHE

Hardening and Embrittlement of Reactor Pressure Vessel Steels 2 Orz T 2May

4. FIN OR GRANT NULBER

Y63965. AUrHOR(S) 6. TYPE OF REPORT

G. R. Odette, .E. Lucas, D. Klingensmith, B. D.Wirth and D. Gragg7. PERIOD OOVERED fnciu Dow)

S. PERFORMING ORGANATION - NAME AND ADDRESS (Yr poveOA'axw% earRegmn U& vr.gufbyCamss and mukdg addius: r-&Wbr.pwide ame mud mei addres)

Department of Mechanical and Environmental EngineeringUniversity of California Santa BarbaraSanta Barbara, CA 93106

S. SPUORMN ORGANIZATION- NAM AN AnOESS PF#, a m s &twtcc*cr pr,d9=kW Cfflwbg Ooia U..s NRWd9f9fbuffLan weft ad*frSs)

Division of Engineering TechnologyOffice of Nuclear Regulatory ResearchU.S. Nuclear Regulatory CommissionWashington, DC 20555-0001

10. SUPPLEMETARY NOTES

C. Santos, NRC Project Manaaer11. ABSTRACT MM *vds brss)

This report addresses several important issues regarding possible revisions of RG 1.99 Rev. 2 to predict irradiationinduced hardening (y) and hence embrittlement manifested as shifts (AT) in the 41 J Charpy test transitiontemperature. We are developing a Acy database from controlled, single-variable experiments to map the individualand interactive effects of metallurgical and environmental variables.The data are generated from a large matrix ofcomposition-controlled alloys Irradiated in the Irradiation Variables Fadlity (IVAR) at the University of Michigan FordResearch Reactor.The results provide quantitative and Independent validation of the two component form of theNUREG/CR-6551 model, comprised of matrix feature (MF) and copper rich precipitate (CRP) terms. The IVAR databasealso quantitatively supports: 1) the model treatments of a strong copper-nickel interaction in the CRP term; 2) thetreatment of phosphorous in the MF term; 3) an independent validation of a maximum effective matrix copper level(Cumax) of around 03% following heat treatment and 4) a sensitivity of Cumax to nickel content.The IAR databasealso shows: 1) manganese interaction with copper and nickel in the CRP contribution; 2) manganese and nickelIncrease the MF term; 3) a somewhat unanticipated effect of flux and flux-composition interactions on the fluencedependence of AMy and AT; and 4) a possible reduction in the effect of phosphorus at higher copper.

12. KEY WOD SAE S .d. -RO "rs rs w,ss w l in . iH r) 1& AVALABLnrY STAEMENr

Reactor Pressure Vessel, Embrittlement, unEmfeEmbrittlement Mechanisms

(This Ave)

unclassified(Ihrs Rep"~

unclassified15. NLLIBER OF PAGES

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NUREG/CR-6778 THE EFFECTS 0F COMPOSITION AN!) H1EAT.REATMENT' N HARDEINING ANDEMBRITTLEMENT OF REACTOR PRESSURE VESSEL STEELS

UNITED STATESNUCLEAR REGULATORY COMMISSION

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MAY 2003

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