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Durability Analysis
Detailed Analysis Agenda
• Background: Fatigue Analysis
• Durability Analysis for
– Blockcycle Testing
Test Acceleration– Test Acceleration
– Correlation
Fatigue Life Analysis Methods
Total Life Method: S – N l
(Stress Life/Load Life/Generic Load Life)og S
)log()log()log( NkASANS k +==
log N
εCrack Initiation Method: e - N
log N
(Strain Life) db cNaN +=ε
Stress-Life Curves
• Generic Stress Life
– Stress life/Load Life approach
– Specify a Y-axis intercept and slope
– Amplitude to life is linear Amplitudep(for a segment)
Typically used for A B
Amplitude
– Typically used for A-B comparisons
Life
Strain-Life Curves
• Strain-Life– Data found in lookupData found in lookup
tables e.g. SAE– Use for true strain data– Estimates life to crack
initiation– Units supported are SI, pp ,
USC and KGF
Damage Calculations
• Damage can be calculated from two sources:– Time historyTime history– Histogram
• Damage can be represented in the following form:– Damage listing
Damage Time history– Damage Time history– Damage Histogram
Damage Calculations• Damage calculation process - 1
1-1. Identify first cycle
log S
log N
1 2 Calculate damage (passes to failure)1-2. Calculate damage (passes to failure)
2-1. Identify next cycle …. Through to last cycle
log S
log N
2-2. Calculate damage (passes to failure)
Damage Calculations
• Damage calculation process – 2
•DamageTotal = (Damagecycle1+Damagecycle2+ …. +DamagecycleN)
• Palmgren-Miner Rule– Damage per cycle identified from S-N curve– Total damage is the sum of each cycle’s damageTotal damage is the sum of each cycle s damage– Life is inverse of sum of damage
Standard Fatigue Features
The following is a summary for the standard fatigue analysis features available in Analyze:
– Materials library– Fatigue sensitive editing
– Rainflow counting– Range Pair countingFatigue sensitive editing
– Local stress/strain life prediction
– Stress life prediction
Range Pair counting– Level crossing analysis– Rosette analysis– Peak valley slicingSt ess e p ed ct o
– Mean Stress Correction– Damage calculations– Notch factor analysis
Peak valley slicing– Rainflow regeneration– Peak valley regeneration– Histogram accumulationNotch factor analysis
– Scale factor analysisHistogram accumulation
– Histogram editing
Analyze
• Data formats supported:
– Native file format is RPC format• This is the defacto-standard in the testing
industry
– Somat SIF filesSomat SIF files
– nCode DAC files
– ASCII data (time history and matrix)
Agenda
• Background: Fatigue Analysis
• Durability Analysis for
– Blockcycle Testing
Test Acceleration– Test Acceleration
– Correlation
Accelerated Durability Testing – Simple Cyclic
Range-Mean Material PropertiesMeasured
Service Strainεm
gRainflow Matrix ε
Material Properties
εrN
Calculate fatigue damageCalculate fatigue damage
Sε
Adjust applied load to achieveselected strain level t
Cyclic Test N
Select strain level d l Loadand cycle count
Equivalent Damage
• Equivalent Amplitude– Back calculate a constant
amplitude profile which yields the same damage as the time history
– Two modes:• User defined amplitude
U d fi d l• User defined cycles
Peak Picking/Peak Valley Slicing
Modes supported:
• Peak Picking – Peak Valley Slicing ToolModes supported:
Peak Pickingonly valid for a single channel test –phase is not maintained
Peak SlicingUse for accelerating tests and compressing data (reduce the size of data files required for fatigue analysis)data files required for fatigue analysis)
Peak Pick FlexTest ProfileOr
RPC Time History
Accelerated Durability Testing – Block Cycle
Range-Mean Material PropertiesMeasured
Service Strainεm
gRainflow Matrix ε
Material Properties
ε0εrN
ε0
εεm
εr
ε0
St
ε
Adjust applied loads to achieve
Remove strain rangesbelow fatigue limit
t
Block cycle
Develop equivalent block cycle strain history
Adjust applied loads to achieveselected strain levels test load
Manual Block Cycle Test Definition
• Histogram Editing – applications– Component test generation
Export to Excel for further analysis and block cycle definition
Histogram Editing• Histogram Editor – fatigue sensitive editing
1. Select Rainflow Histogram
2. Configure Damage3. Calculate Damage
Histogram Editing
• Histogram Editor – fatigue sensitive editing
Black = RainflowBlue = Damage
4. Enter editing criteria & Edit
Fatigue Sensitive Editing will remove the least damaging content bin-by-bin until the user specified criteria is met.
Histogram Editing
• Histogram Editor – fatigue sensitive editing
Black = Rainflow - editedBlue = Damage
5. Output edited Rainflow
Block Cycle Generator
1. Select Rainflow Histogram
2. Review Cyclic and Damage Content
Block Cycle Generator : Zero Bins
1. Define Damage to Retain
2. Run Editing Function
3. Review Resulting Cyclic and Damage Content
Block Cycle Generator : User Defined Bins
1. Define Bins
2. Run Editing Function
3. Review Resulting Cyclic and Damage Content
Block Cycle Generator : Create Profile
1. Define Ordering2. Define Output Type3. Run the creation step
4. Review Resulting Profile
Rainflow Regeneration• Histogram Editing – applications
– Component test generation from edited rainflow histograms – Rainflow Regenerationhistograms – Rainflow Regeneration
Only applicable for single channel tests
Export to Excel for further analysis and block cycle definition
Agenda
• Background: Fatigue Analysis
• Durability Analysis for
– Blockcycle Testing
Test Acceleration– Test Acceleration
– Correlation
Why Edit the Measured Data?• Goal of simulation: reproduce the damage caused by
the road in a controlled environment.• Goal of editing: accelerate test• Goal of editing: accelerate test
C t UCustomer UsageWhy Edit? :
• Shorten test time
Test Track• Remove non-
damaging data
• Remove physically
T L b
physically unrealizable data
Test Lab
Selection of Test Profiles
• Test Profile Selection– Customer Correlation
• Ultimately the goal of any test is to test a sample of products to a customer correlated lifeS l Ch ll i• Several Challenges exist:
– Many different types of customerMany different driving– Many different driving environments
Proving Ground events
• Pave or Belgian Block• Washboard• Pot Holes– Proving Ground events
• Not all events will be meaningful for all components
• Pot Holes• Curb Strikes• Rough Road• Cross Country
– Need a methodology for selecting the most representative tests
• Ride & Handling• Other Special Events
Selection of Test Profiles
• Test Profile Selection
– Damage Assessment Analysis• RPC Test Profile selection wizards
Facilitate selection of events before file based– Facilitate selection of events before file based editing
– Damage and time criteria
– Purpose of analysis:• Allow user to modify test sequence contents
(profiles and passes) to retain damage but reduce time
• Report correlation of edited data to raw test• Report correlation of simulated data to raw test
Selection of Test Profiles –Damage Assessment Analysis• Results
Simulated DataIndividual Damage
acc_fw_1_twist_1_R shock_1_Rripple_1_Racc_bk_1_inner_1_Rcob_1_RSScale1 E B ktV t 00006 00008 0094 2 25
Original Raw Data
1 EngBrktVert .00006 .00008 .0094 2.252 EngBrktLat .00186 .00341 .0152 60.3 EngBrktLng .00379 .00831 .00335 2.375
All Channels .00572 .0118 .02795Time
acc_fw_1_twist_1_R shock_1_Rripple_1_Racc_bk_1_inner_1_Rcob_1_RSCumulativeTime (sec) 300 625 2520 3445
SimulatedTime
Edited Data
Time (sec) 300 625 2520 3445Time Contribution 8.71% 18.14% 73.15%Deleted 71.43% 83.33% 62.5% 78.2%
Cumulative Damageacc_fw_1_twist_1_R shock_1_Rripple_1_Racc_bk_1_inner_1_Rcob_1_RSCumulative
1 EngBrktVert .00193 .00201 .78955 .793492 EngBrktLat .0558 .0853 1.27716 1.41827
eComparisonto Raw
Simulated Data
2 EngBrktLat .0558 .0853 1.27716 1.418273 EngBrktLng .11381 .20772 .28136 .60289
All Channels .17154 .29503 2.34807 2.81464Cumulative Contribution
acc_fw_1_twist_1_R shock_1_Rripple_1_Racc_bk_1_inner_1_Rcob_1_RSP_12ch_sim1 EngBrktVert 0.24% 0.25% 99.5%2 EngBrktLat 3.93% 6.01% 90.05%
Damage Retention
3 EngBrktLng 18.88% 34.45% 46.67%All Channels 6.09% 10.48% 83.42%
Retained Damageacc_fw_1_twist_1_R shock_1_Rripple_1_Racc_bk_1_inner_1_Rcob_1_RSCumulative
1 EngBrktVert 70.22% 67.89% 81.66% 80.74%2 EngBrktLat 126.18% 126.18% 120.03% 120.12%
Simulated DamageComparisonto Raw3 EngBrktLng 61.24% 58.14% 56.17% 57.39%
All Channels 73.68% 68.96% 92.74% 87.57%Max 126.18% 126.18% 120.03% 120.12%Min 61.24% 58.14% 56.17% 57.39%Avg 85.88% 84.07% 85.95% 86.08%
to Raw
Selection of Test Profiles –Damage Assessment Analysis
• Results
Cumulative Rainflow(Exceedance Plot)
Cumulative Damage(Summation Plot)
Data Editing
• RPC offers the following editing methods
– Graphical / Manual editing
– Statistical based editing
Fatigue based editing– Fatigue based editing
Graphical Editing• Graphical Editing Procedure
– Graphically select the data you wish to edit using the mouse (user selections are illustrated in red)the mouse (user selections are illustrated in red)
M t h i t d f i d– Many techniques supported for removing and re-joining data at edit boundaries.
Advantages and Disadvantages
• Graphical Editing
– Advantages:• Interactive – user has full control• Fast on small data files• Easily undo/redo edits
– Disadvantages:• Interactive – cannot readily automate• Takes more time on larger, more complex
datasetsdatasets• Difficult to document editing criteria
Statistical Editing Tools
• Perform statistical selections on a time historyy
– Mark regions (sections of time history) to edit based onhistory) to edit based on Statistical criteria
– Use criteria based on Max/Min, RMS, Damage, etc
– The marking limits can either be defined as percentage of full scale or in absolute values.O ti ll lti l it i– Optionally use multiple criteria on different channels with logical operators
Statistical Editing Example
• Example with three channels of strain data. (Note this technique can be applied to any time history data.)q pp y y )
- Raw Data
Statistical Editing Example
• Statistical Editor Wizard
1. User enters input data file & defines output
1. Select statistic and comparison.
3. Define the threshold and if it is engineering unit or percent.
4. Define window size.
In the example configuration above we are attempting to:− select 1 second windows− where the max value within that windows is less than 30% of the overall max
Statistical Editing Example
• Individual Channel Results:
− Note: the regions (the blue sections) have been selected different for each channel. g ( )− To preserve phase in multi channel data we must combine the independent regions.
Statistical Editing Example
• Combined Region Result:
After combining the individual channels into a time line region file we can edit the data − After combining the individual channels into a time line region file, we can edit the data. − The next figure shows the edited output compared against the unedited input.
Statistical Editing Example
• Edited Result:
Channel 1
Channel 2
Channel 3
Black: Raw unedited dataBl Edit d d tBlue: Edited data
Advantages and Disadvantages
• Statistical Editing
– Advantages:• Automation • Easy/quick to edit even larger data files• Can combine multiple editing criteria• Can manually “fine tune” results• Can manually fine tune results• Consistent editing procedures can be defined
– Disadvantages:• May not be intuitive
Additi l l i b i d t• Additional analysis may be required to achieve time reduction goals
Damage Time History
• Damage is calculated for every peak-valley cycle, the damage time history is generate by assigning damage g y g y g g gto location of the peak and valley.
Peak – valley pair
Peak – valley pair
Damage Time History
• Fatigue Sensitive Editing:
Edit time history data based Damage time historyon regions selected from thedamage time history
shows where damagingcycles occur in the data
Fatigue Sensitive Editing
• Automatic Damage Editor (ADE)
– The ADE tool is a fatigue sensitive editor and allows the user to accurately and automatically
d th l th f d t fil i d freduce the length of data files required for simulation.
– By specifying a desired damage retention percentage, the tool will iterate to an optimum solution balancing damage retention with timesolution balancing damage retention with time reduction.
Th ADE l th t f D– The ADE leverages the concepts of Damage Time History and Statistical Editing
Fatigue Sensitive Editing
ADE Tool –editing configuration
Use the Automatic Editing tab to gspecify a desired percentage of damage retention.
Fatigue Sensitive Editing
window
• Automatic Damage Editor Tool – executionwindow
tolerance
The damage time history (blue) represents the per cycle occurrence of damage - The damage time history (blue) represents the per cycle occurrence of damage in the strain road data (black)
- Regions are selected by statistically processing the damage time history and comparing against a tolerance valuep g g
- If the damage is less than the tolerance the window is selected for deletion- The tolerance value is automatically adjusted to “iterate” to a solution
Fatigue Sensitive Editing
• Automatic Damage Editor Tool – reporting results
The report isThe report is automatically updated every pass of the ADE tool.tool.
Fatigue Sensitive Editing
• Automatic Damage Editor Tool – reporting results
Color highlight is g gused to indicate the progress of each channel, red indicates channels out of criteria while green indicated those channels that are withinthat are within criteria.
Fatigue Sensitive Editing
• Automatic Damage Editor Tool – selected regions
Regions markedmarked for deletion
Fatigue Sensitive Editing
• Automatic Damage Editor Tool – final output
Raw and Edited Time History
Fatigue Sensitive Editing - Example
• Objective: to perform fatigue sensitive editing on data provided by a customer to establish total durability p y ytest time and the amount of feasible test time reduction while maintaining adequate fatigue content of the raw road data.of the raw road data.
– Four test cases are evaluated:• Analysis of original customer editing (RMS
based)based)• 99% fatigue retention• 95% fatigue retention• 20 hour test
Fatigue Sensitive Editing - Example
T t Ti R d ti
Result Summary
Test Time Reduction
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
% Original Test
Raw Test
St ti ti lStatistical Editing
99% DamageRetention Retention
95% Damage Retention
Fatigue Sensitive Editing - Example
• Customer Editing (Test time = 183.1 hrs Time Reduction = 68%)Case: Customer Editing
Damage Analysis
Channel Raw damage Edited damage RetentionX 4.52E-02 4.49E-02 99.3%Y 2.31E-02 2.30E-02 99.4%Z 1.37E-01 1.31E-01 95.7%
Average Retention 98.1%
LevelcrossLevelcross of raw and edited data
Black = RawBlue = EditBlue Edit
Fatigue Sensitive Editing - Example• 99% damage retention (Test time = 151.3 hrs Time Reduction
= 74%) Case: 99% Fatigue Retentiontollerence = +/- 0.5%Channel Raw damage Edited damage RetentionX 4.52E-02 4.47E-02 98.9%Y 2.31E-02 2.29E-02 98.9%Z 1.37E-01 1.35E-01 98.8%
Damage Analysis
Average Retention 98.9%
LevelcrossLevelcross of raw and edited data
Black = RawBlue = EditBlue Edit
Fatigue Sensitive Editing - Example• 95% damage retention (Test time = 122.8 hrs Time Reduction
= 79%)Case: 95% fa tigue retentiontollerence = +/- 2%Channel Raw damage Edited damage RetentionX 4.52E-02 4.37E-02 96.7%Y 2.31E-02 2.19E-02 95.0%Z 1.37E-01 1.30E-01 95.2%
Damage Analysis
Average Retention 95.6%
LevelcrossLevelcross of raw and edited data
Black = RawBlue = EditBlue Edit
Fatigue Sensitive Editing - Example
Case: 20hr Test
• 20 Hour Test (Test time = 22 hrs, Time Reduction = 96%, Fatigue Retention = 29%)
Channel Raw damage Edited damage RetentionX 4.52E-02 1.43E-02 31.6%Y 2.31E-02 6.69E-03 28.9%Z 1.37E-01 3.69E-02 26.9%
Damage Analysis
Average Retention 29.1%
LevelcrossLevelcross of raw and edited data
Black = RawBlue = Edit
Note: This level of test acceleration was Blue Editunacceptable because of the poor fatigue retention.
Fatigue Sensitive Editing - Example• Comparison of retained damage – histogram
analysis (Raw)
Fatigue Sensitive Editing - Example• Comparison of retained damage – histogram
analysis (99%)
Fatigue Sensitive Editing - Example• Comparison of retained damage – histogram
analysis (20Hr)
Fatigue Sensitive Editing
• Fatigue Sensitive Editing Summary
– Fatigue Sensitive Editing is an alternative editing approach which is accurate and efficient.
– The Automatic Damage Editor allows users understand the trade-off of test time reduction and damage retention.
Agenda
• Background: Fatigue Analysis
• Durability Analysis for
– Block Cycle Testing
Test Acceleration– Test Acceleration
– Correlation
Why Validate the Test Results?• Goal of simulation: reproduce the damage caused by the road
in a controlled environment.• Goal of validation: Prove that you have replicated the test track.y p
C t UCustomer UsageWhy Validate? :
• Defend your test results.
Test Track• Learn where
improvements are needed.
T L b
• Gain confidence in accuracy of models.
= ?Test Lab
Basis for Correlation
• Correlation Sensors– Sensors (load, strain, acceleration, etc) which are
measured but are not used as part of the Control Setmeasured but are not used as part of the Control Set
• Approach– Very similar to test accelerationVery similar to test acceleration
• Tools For Correlation– Visual Inspectionp– Rainflow Analysis– Fatigue Analysis– Frequency Analysis– Statistical Analysis– Level Crossing Analysis
Basis for Correlation
• test_timehistory: measured data from test• target timehistory: “desired” data from PGtarget_timehistory: desired data from PG
Visual Inspection
Visual Inspection
Rainflow Analysis
Damage Assessment Analysis
• ResultsSimulated DataIndividual Damage
acc_fw_1_twist_1_R shock_1_Rripple_1_Racc_bk_1_inner_1_Rcob_1_RSScale1 E B ktV t 00006 00008 0094 2 25
Original Raw Data
1 EngBrktVert .00006 .00008 .0094 2.252 EngBrktLat .00186 .00341 .0152 60.3 EngBrktLng .00379 .00831 .00335 2.375
All Channels .00572 .0118 .02795Time
acc_fw_1_twist_1_R shock_1_Rripple_1_Racc_bk_1_inner_1_Rcob_1_RSCumulativeTime (sec) 300 625 2520 3445
SimulatedTime
Edited Data
Time (sec) 300 625 2520 3445Time Contribution 8.71% 18.14% 73.15%Deleted 71.43% 83.33% 62.5% 78.2%
Cumulative Damageacc_fw_1_twist_1_R shock_1_Rripple_1_Racc_bk_1_inner_1_Rcob_1_RSCumulative
1 EngBrktVert .00193 .00201 .78955 .793492 EngBrktLat .0558 .0853 1.27716 1.41827
eComparisonto Raw
Simulated Data
2 EngBrktLat .0558 .0853 1.27716 1.418273 EngBrktLng .11381 .20772 .28136 .60289
All Channels .17154 .29503 2.34807 2.81464Cumulative Contribution
acc_fw_1_twist_1_R shock_1_Rripple_1_Racc_bk_1_inner_1_Rcob_1_RSP_12ch_sim1 EngBrktVert 0.24% 0.25% 99.5%2 EngBrktLat 3.93% 6.01% 90.05%
Damage Retention
3 EngBrktLng 18.88% 34.45% 46.67%All Channels 6.09% 10.48% 83.42%
Retained Damageacc_fw_1_twist_1_R shock_1_Rripple_1_Racc_bk_1_inner_1_Rcob_1_RSCumulative
1 EngBrktVert 70.22% 67.89% 81.66% 80.74%2 EngBrktLat 126.18% 126.18% 120.03% 120.12%
Simulated DamageComparisonto Raw3 EngBrktLng 61.24% 58.14% 56.17% 57.39%
All Channels 73.68% 68.96% 92.74% 87.57%Max 126.18% 126.18% 120.03% 120.12%Min 61.24% 58.14% 56.17% 57.39%Avg 85.88% 84.07% 85.95% 86.08%
to Raw
Frequency Analysis
Statistical Analysis
15
5
10
Target
10
-5
0
Max
imum
Minim
um
Mea
n
Varian
ce
Std D
ev
RMS
Crest
Sum
Kurtos
is
Skew
gTest
-15
-10
Level Cross Analysis
• How many times does the signal cross each level?
RPC Pro – Reporting
• Time History Report Tool– Template based ReportTemplate based Report
Generation– Fully customizable
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