About this Abstract |
Meeting |
2024 ASC Technical Conference, US-Japan Joint Symposium, D30 Meeting
|
Symposium
|
2024 ASC Technical Conference, US-Japan Joint Symposium, D30 Meeting
|
Presentation Title |
Modeling Fatigue Performance of Short Fiber Reinforced Plastics |
Author(s) |
Almambet Iskakov, Surya R Kalidindi, Ana Rodriguez Sanchez, Jan-Martin Kaiser, Matthias De Monte |
On-Site Speaker (Planned) |
Almambet Iskakov |
Abstract Scope |
Characterization of fatigue life of Short Fiber Reinforced Plastics (SFRP) for engineering applications is both costly and time-consuming. Typically, such efforts involve a large number of tests to cover the large test space corresponding to various combinations of testing conditions and sample notch geometries for a single grade of SFRP. In this study, we propose a framework aimed at reducing the number of expensive experiments required to estimate the fatigue life behavior for SFRP grades at various test conditions and notch geometries. Our approach is based on training on a sparse set of experimental fatigue tests of various SRFP grades to estimate a broader fatigue behavior at different test conditions for each grade. Microstructure descriptors based on fiber orientations extracted from experimental microCT (microcomputed tomography) 3D images and are feature engineered based on test conditions. The modeling step leverages multi-output Gaussian process (MOGP) to model linear fit S-N curve parameters at different test conditions. Application of the framework is demonstrated on a number of SFRPs grades with various combinations of fiber fractions, fatigue test load ratios, loading angles, temperatures, and notch geometries. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |