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