monaco/mavric: computational resources for radiation protection and shielding in scale douglas e....

Monaco/MAVRIC: Computational Resources for Radiation Protection

and Shielding in SCALE Douglas E. Peplow, Stephen M. Bowman, James E. Horwedel, and John C. Wagner

Nuclear Science and Technology DivisionOak Ridge National Laboratory

Computational Resources for Radiation Protection and Shielding - IIAmerican Nuclear Society Winter Meeting

November 16, 2006 Albuquerque, New Mexico

2

OAK RIDGE NATIONAL LABORATORYU. S. DEPARTMENT OF ENERGY

Introduction

Monaco — multi-group Monte Carlo code MORSE physics SCALE Generalized Geometry Package (same as KenoVI)

MAVRIC — Automated Variance Reduction CADIS Methodology GTRUNCL3D and TORT Monaco for Monte Carlo Calculation

GeeWiz — the Windows GUI for using many SCALE programs

Monaco/MAVRIC will be part of SCALE 6

3


SCALE

Standardized Computer Analyses for Licensing Evaluation

Collection of codes for performing criticality safety radiation shielding spent fuel characterization reactor physcis radiation source terms and decay heat

4


SCALE

Functional modules – physics calculations KENO, Monaco, ORIGEN-S, NEWT, XSDRNPM

Control modules automate the execution and data exchange of individual codes to perform various types of analyses in calculation sequences CSAS, MAVRIC, TSUNAMI, TRITON

Multi-group and continuous energy cross-section data

5


Current SCALE Shielding Modules SAS1 – 1-D discrete ordinates Shielding Analysis Sequence

automates cross-section processing, transport calculation, and calculation of dose rates outside a defined shield

Combined 1-D criticality/shielding analysis (e.g. CAAS)

SAS4 – 3-D Monte Carlo Sheilding Analysis Sequence designed for calculation of radiation doses exterior to a transport/storage cask. Uses XSDRNPM to calculate adjoint fluxes for the generation of biasing parameters

MORSE 3-D Monte Carlo functional module used in SAS4 Different geometry package than the SCALE Monte Carlo

criticality (KENO) codes Legacy code, geometry package has not been updated in >20

years

6


Current SCALE Monte Carlo Shielding

SAS4 – Shielding Analysis Sequence Automated 1-D axial or radial variance reduction Not updated in more than a decade

Design limitations based on cylindrical cask geometry Effective for cask mid-plane and top center doses Not well suited to cask corners or very

heterogeneous geometries Not effective for general purpose shielding

analyses Hence, need for modern Monte Carlo tool with

automated 3-D variance reduction (AVR) for general shielding applications

7


Monaco

3-D Multi-group Monte Carlo MORSE physics SCALE Generalized Geometry Package (same

as KenoVI)

Fixed source Variety of geometric shapes Can use a mesh-based source

Tallies Point detectors, region tallies, mesh tally Convolves fluxes with detector responses

8


Monaco

Variance Reduction Biased source energy distribution Source direction distribution Path length stretching Point detector tallies Weight windows by region and energy group

Advanced Variance Reduction Mesh/energy group based importance map Mesh/energy group based biased source

9


Monaco Example: Ueki Experiment

10



Table 6. Comparison of two hour results

0.1

1

10

100

1000

0 10 20 30 40 50Thickness (cm)

Dos

e E

quiv

alen

t Rat

e (µ

Sv/h

r)Measured

Monaco

Figure 3. Two hour results comparison

11



12


MAVRIC

3-D Automated Variance Reduction

SCALE cross section processing

GTRUNCL3D and TORT Computes the adjoint flux for a given response

Monaco for Monte Carlo calculation Importance map (weight windows for splitting

and roulette) Biased source distribution

13


CADIS Methodology

From the adjoint flux Importance map for MC transport (weight windows

for splitting and roulette) Biased source distribution

Biased source and importance map work together (i.e., are consistent)

A. Haghighat and J. C. Wagner, “Monte Carlo Variance Reduction with Deterministic Importance Functions,” Progress in Nuclear Energy, 42(1), 25-53, (2003).

Consistent Adjoint Driven Importance Sampling

14


CADIS Methodology

Want to find:

Erq ,

source emission probability distribution function (pdf)

S total source strength

),( Era

absorption cross section

),( Ers scattering cross section

),( Erd

detector response function

typical problem:

),( Er

Or some detector response related to flux:

flux

E V

d dVdEErErR ,,

15


CADIS Methodology

If the adjoint flux for a given detector response is known:

Then the detector response is simply:

),( Er

E V

dVdEErErqSR ,,

Unfortunately, the exact adjoint flux may be just as difficult to determine as the forward flux.

16


CADIS Methodology

With an approximate adjoint flux for a given detector response:

),( Er

Total detector response is approximated as:

Biased source distribution found to be:

Sampled particles start with weights of:

E V

dVdEErErqSR ,,

SR

ErErqErq

),(),(),(ˆ

),(),(0 Er

SRErw

17


CADIS Methodology

Weight window target weight values:

),(),(

Er

SRErw

Weight window size: (c=upper/lower)

lwc

w

2

1

18


SCALE Sequence: MAVRIC

Cross sections Multi-group SCALE libraries Create adjoint and forward cross section sets

Find the approximate adjoint flux GRTUNCL3-D – first collision code (for pnt det) TORT – 3-D discreet ordinates transport code

Forward Monte Carlo - Monaco Uses mesh-based biased source Uses mesh-based importance map (weight windows)

Automate as much as possible

An implementation of the CADIS Methodology

19


SCALE Sequence: MAVRIC

Monaco with Automated Variance Reduction using Importance Calculations

SCALEDriverandMAVRIC

Input

ICE

Monaco

End

Optional: TORT adjoint cross sections

Optional: 3-D discrete ordinates calculation

3-D Monte Carlo

Resonance cross-section processing

BONAMI / NITAWL orBONAMI / CENTRM / PMC

TORT

GRTUNCL-3D Optional: first-collision source calculation

20


MAVRIC Example – Weight targets

21


MAVRIC Example - Source Biasing

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0 2 4 6 8 10Energy (MeV)

Prob

abil

ity

per M

eV

True

Biased

22


MAVRIC Example Results

FOM FOMThickness Monaco MAVRIC speedup

(cm) (/sec) (/sec)0 2.35E+02 1.11E+03 55 5.66E+00 1.30E+02 2310 2.15E+00 7.13E+01 3315 9.12E-01 2.94E+01 3220 4.40E-01 2.38E+01 5425 2.60E-01 2.19E+01 8430 1.16E-01 1.70E+01 14735 6.90E-02 1.49E+01 21640 3.79E-02 9.52E+00 25145 1.41E-02 1.37E+01 96750 5.68E-03 1.15E+01 2027

21

TFOM

23


MAVRIC Cask Example

24


MAVRIC Cask Example

25


MAVRIC Cask Example

26


MAVRIC Cask Example

TORT Monaco

1142 1.50E-09 (2.92%) 4.52E-06 (39.90%)

70 121 1.49E-09 (0.23%) 4.91E-06 (4.05%)

time (min)

uncollided total

Neutron dose rate (rem/hr)

Speed up: 583

27


MAVRIC Cask Array Example

28



29



TORT Monaco

1083 3.45E-09 (0.84%) 2.83E-05 (6.33%)

44 664 3.08E-09 (0.13%) 2.91E-05 (1.47%)

time (min)

uncollided total

Neutron dose rate (rem/hr)

Speed up: 28

30



31


GeeWiz

32


KENO3D

Powerful 3-D interactive visualization tool that displays KENO V.a or KENO-VI geometry models

Plot calculated results (e.g., fluxes and reaction rates) over geometry

33


KENO3D

help top view, side view toggle wireframe toggle highlight edges orbit rotate pan zoom options axis legend simple cuts rebuild in window dockable toolbars

34


Future Work

MAVRIC Sequence Automatic homogenization in importance map Refine standard set of TORT parameters Incorporate new Monaco tallies Optimizing mesh tallies

Monaco Modern F95 programming structures Modern, block/keyword input structure Output to separate (html) tables Larger variety of source descriptions Larger variety of tally options – multipliers, totals

Cross-Section Data ENDF/B-VI coupled multigroup library

Testing, Testing, then a bit more Testing

Discussion & Questions

monaco/mavric: computational resources for radiation protection and shielding in scale douglas e....

Documents

monte carlo calculationgeewiz

modern monte carlo tool

d axial

department of energymonaco3

scale douglas

scale programsmonacomavric

d variance reduction

sas4different geometry