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Leverage reinforced plastics durability prediction, from calibration to post-processing
- 1. Leverage reinforced plastics durability prediction, from calibration to post-processing Webinar, 18th September 2019 DSM load bracket fatigue demonstrator Pierre Savoyat Digimat Product Manager pierre.savoyat@e-xstream.com Lucien Douven Research Scientist / Design Engineer lucien.douven@dsm.com
- 2. Confidential2 We are about to release Digimat 2019.1
- 3. Confidential3 Witness integrative approach results targeting structural application DSM load bracket fatigue demonstrator
- 4. Confidential4 Testing and calibration are challenging, predictions are much too conservative
- 5. Confidential5 Rely on accurate fatigue failure indicator and easily interpret FEA simulation results to compute part lifetime
- 6. Confidential6 Use Digimat to reach accurate SFRP fatigue lifetime predictions Dedicated environment for fatigue failure indicator calibration Dedicated environment for fatigue lifetime computation Partner to push limits
- 7. Confidential7 e-Xstream engineering is the right partner to push SFRP fatigue prediction limits
- 8. Confidential8 DSM Engineering Plastics One of the key material suppliers in automotive and electronics You can find DSM materials in 87% of all cars
- 9. Confidential9 Goal : Implement DSM framework in e-Xstream’s Digimat tools • Enable more accurate part fatigue lifetime predictions • Improve efficiency and accuracy to calibrate and validate material cards for high cycle fatigue (Digimat-MF, Digimat-MX) • Enable DSM customers by providing an efficient workflow for part fatigue lifetime evaluation (Digimat-RP) So how about the prediction results ? DSM / e-Xstream collaboration Improving SFRP fatigue lifetime prediction
- 10. Confidential10 Framework CAE fatigue prediction Flow simulation Fatigue data Digimat material model Part prediction Stress concentration correction R-value dependence Anisotropy Microstructure Glass fiber orientation Notch sensitivity A full overview will be presented at the Digimat User’s Meeting, October 2019 This webinar
- 11. Confidential11 Microstructure comparison Over the path at this location (near failure location), the measured fibre orientation and predicted orientation (Moldflow V2019) correspond well. Milled and CT- scanned domain Failure location Fiber orientation at failure location is predicted well
- 12. Confidential12 Part level – Experimental data 0.5 0.1 -0.5 -1 -2𝑅 𝐹 = 𝐹 𝑚𝑖𝑛 𝐹𝑚𝑎𝑥 PA66 GF50, DAM, 23°C Load bracket test data Nf,
- 13. Confidential13 Part level – Local stress ratio PA66 GF50, DAM, 23°C F = -1500 N F = 1500 N 𝜎 𝑚𝑖𝑛 = −34.3 𝑀𝑃𝑎 𝑅 = 𝐹 𝑚𝑖𝑛 𝐹𝑚𝑎𝑥 𝑡 𝐹 < 0 𝐹 > 0 𝐹 𝜎 𝑚𝑎𝑥 = 94.3 𝑀𝑃𝑎 𝑅 𝜎 ≠ −1
- 14. Confidential14 Part level – Local stress ratio PA66 GF50, DAM, 23°C 𝑅 = 𝐹 𝑚𝑖𝑛 𝐹𝑚𝑎𝑥 𝑡 𝐹 < 0 𝐹 > 0 𝐹 Local stress ratio The local stress ratio is not equal to the applied load ratio. The local stress ratio also depends on the magnitude of the load One needs to correct for the local stress ratio to enable accurate liefetime predictions! 𝑅 = −1 𝑅 = −2 𝑅 = −0.5 𝑅 = 0.1 𝑅 = 0.5 failure location 1 𝑅 ≥ −1 failure location 2 𝑅 < −1
- 15. Confidential15 Part level – Local stress ratio PA66 GF50, DAM, 23°C anisotropy x R-value x stress concentration x GF prediction (ans o3ro x -va3 e x stre ss co5centrtion x G?ic =45 x ?) x10 overestimation x3 /3 /10 • Failure location captured • Predictions of complex parts with accuracy of factor 5-30x for most R-values. • R-value dependence accurately captured safe Load bracket
- 16. Confidential16 We keep pushing now accounting for local plasticity Stress Strain න 𝜀𝑖𝑗 𝑒 𝑑𝜎𝑖𝑗 𝑒 = න 𝜀𝑖𝑗 𝑒𝑝 𝑑𝜎𝑖𝑗 𝑒𝑝 3D extension of ESED rule Glinka correction Elastic Elastoplastic • Maintained CPU time Perform the same elastic simulation • Enriched inputs for lifetime computation Estimate plastic stress field Compute new local R × 𝐾𝑓 Fatigue data notched specimensFEA results 0°, 0.25mm, R=-1 DSM communication at SPE ACCE 2019
- 17. Confidential17 overestimation Load bracket safe x10 x3 /3 /10 Plasticity and stress gradient correction allow to reach targeted results at part level. • Failure location captured • Predictions of complex parts within 1 decade. • R-value dependence accurately captured Part level – Plasticity correction results PA66 GF50, DAM, 23°C
- 18. Confidential18 overestimation fine mesh (0.1mm) coarse (0.75mm) intermediate (0.5mm) Load bracket safe x10 x3 /3 /10 Plasticity and stress gradient correction allow to reach targeted results at part level. • Failure location captured • Predictions of complex parts within 1 decade. • R-value dependence accurately captured • Robust to mesh size Part level – Mesh size robustness PA66 GF50, DAM, 23°C
- 19. Confidential19 Digimat-MX: DSM cards for high cycle fatigue prediction PA66 GF50 PPA GF50 Two material cards available on request to perform structural analyses Next: Confirm good results on more applications, are you interested? DSM / e-Xstream collaboration Improving SFRP fatigue lifetime prediction
- 20. Confidential20 Digimat-MX provides the right environment for fatigue failure indicator calibration
- 21. Confidential21 Similar approach to static failure of SFRP Failure criteria applies at pseudo grain level
- 22. Confidential22 Similar approach to static failure of SFRP
- 23. Confidential23 Digimat-MX provides a dedicated calibration environment Failure trigger Lifetime target Parameters Localization factors Parameter dependencies Load ratio
- 24. Confidential24 Digimat-MX provides the right environment for fatigue failure indicator calibration
- 25. Confidential25 Digimat-RP provides the right environment for fatigue lifetime computation
- 26. Confidential26 Numerical simulations require extreme care to predict part fatigue lifetime Elastic Stress saturation Stress relaxation • Elastic material model • No stress saturation (plasticity) • No stress relaxation (viscous effects) Stress Strain • Geometric simplification drawbacks • Faceting • Non convergence of local extrema Notched coupon stress field under tensile load
- 27. Confidential27 Force Time 𝑰𝒏𝒄. Constant R for all elements Force Time 𝑰𝒏𝒄. 𝒎𝒊𝒏 and 𝑰𝒏𝒄. 𝒎𝒂𝒙 Spatially varying R with result assembly Several workflows allowing a time-accuracy trade off 𝜎 𝑎 and 𝑹 𝝈 𝜎 𝑚𝑖𝑛 𝜎 𝑚𝑎𝑥 𝜎 𝑎 and 𝑹 𝝈 𝜎 𝑚𝑖𝑛 𝜎 𝑚𝑎𝑥 𝜎 𝑎 and 𝑹 𝝈 Force Time 𝑰𝒏𝒄. 𝒊𝒏𝒊𝒕. and 𝑰𝒏𝒄. 𝒆𝒏𝒅 Spatially varying R with full cycle Early design Loading screening Design validation MarcAvailable for :
- 28. Confidential28 Numerous lifetime corrections to account for stress concentration are available Stress gradient Interpolation Correct stress field and re-compute lifetime II I L 𝝈 𝒆𝒇𝒇. = 𝝈 𝒂𝒕 𝑳 No correction Same results as FEA simulation based on stress field Lifetime averaging Average lifetime predictions in log domain over a given volume Stress averaging Average stress over a given volume and re-compute lifetime Stress gradient Linear averaging I II2L 𝝈 𝒆𝒇𝒇. = 𝟏 𝟐𝑳 න 𝟐𝑳 𝝈𝒅𝒙 Correct stress field and re-compute lifetime Stress gradient Tangent I II 𝝈 𝒆𝒇𝒇. = 𝝈 𝒎𝒂𝒙 𝟏 + 𝑳 𝝈 𝒎𝒂𝒙 𝒅𝝈 𝒅𝒙 Correct stress field and re-compute lifetime
- 29. Confidential29 Digimat-RP provides the right environment for fatigue lifetime computation
- 30. Confidential30 Use Digimat to reach accurate SFRP fatigue lifetime predictions Dedicated environment for fatigue failure indicator calibration Dedicated environment for fatigue lifetime computation Partner to push limits
- 31. Confidential31 Benefit from material supplier calibrations • They already feed Digimat-MX database heavily : +27 fatigue material cards in Digimat 2019.1
- 32. Confidential32 Next steps • What’s new ? → Look at Digimat 2019.1 release webinar • Interested ? → Look at our case study and come to us to learn more • Yet customer ? → Benefit from our capabilities and from material cards present in Digimat-MX • Looking for guidance ? → Benefit from our expertise in testing, calibration and simulation
- 33. Leverage reinforced plastics durability prediction, from calibration to post-processing Webinar, 18th September 2019 DSM load bracket fatigue demonstrator Thank you! Q&A Pierre Savoyat Digimat Product Manager pierre.savoyat@e-xstream.com Lucien Douven Research Scientist / Design Engineer lucien.douven@dsm.com