| Hybrid Physics and Machine Learning Modeling for Material Characterization and Failure Analysis N Zobeiry, A Joseph, A Eskandariyun, H Fu, S Brunton, B Alan, M Kabir, ... AIAA SCITECH 2024 Forum, 1526, 2024 | 1 | 2024 |
| A Theory-Guided Machine Learning and Reduced-Order Finite Element Modeling Framework to Accelerate Process Simulation of Aerospace Composite Parts H Fu, N Zobeiry ASME Aerospace Structures, Structural Dynamics, and Materials Conference …, 2023 | 1 | 2023 |
| A Novel Machine Learning Framework for Digital Estimation of Allowables in Aerospace Composites A Eskandariyun, H Fu, A Stere, A Bauer, C Reynolds, M Chengalva, ... ASME Aerospace Structures, Structural Dynamics, and Materials Conference …, 2024 | | 2024 |
| Accelerating Composite Cure Cycle Optimization with Combined Probabilistic Machine Learning and Finite Element Process Simulation H FU, C SCHOENHOLZ, P PORTALES, A ESKANDARIYUN, N ZOBEIRY PROCEEDINGS OF THE AMERICAN SOCIETY FOR COMPOSITES-THIRTY-EIGHTH TECHNICAL …, 2023 | | 2023 |
| Exploring Underlying Correlations in Multi-Fidelity Finite Element Simulations of Open-Hole Tension Tests: A Comparative Study Using Machine Learning A ESKANDARIYUN, H FU, J REINER, R VAZIRI, N ZOBEIRY PROCEEDINGS OF THE AMERICAN SOCIETY FOR COMPOSITES-THIRTY-EIGHTH TECHNICAL …, 2023 | | 2023 |
Navid ZobeiryAssociate Professor, University of Washington在 uw.edu 的电子邮件经过验证
Navid ZobeiryAssociate Professor, University of Washington在 uw.edu 的电子邮件经过验证
Amirali EskandariyunPh.D. Student, University of Washington在 uw.edu 的电子邮件经过验证