4 papers
Deep learning-aided inverse design of porous metamaterials
Phu Thien Nguyen, Yousef Heider, Dennis M. Kochmann +1
The ultimate aim of the study is to explore the inverse design of porous metamaterials using a deep learning-based generative framework. Specifically, we develop a property-variati…
Physics-based Machine Learning for Computational Fracture Mechanics
Fadi Aldakheel, Elsayed S. Elsayed, Yousef Heider +1
This study introduces a physics-based machine learning framework for modeling both brittle and ductile fractures. Unlike physics-informed neural networks, which solve partial diffe…
CNN-powered micro- to macro-scale flow modeling in deformable porous media
Yousef Heider, Fadi Aldakheel, Wolfgang Ehlers
This work introduces a novel application for predicting the macroscopic intrinsic permeability tensor in deformable porous media, using a limited set of micro-CT images of real mic…
Phase field cohesive zone modeling for fatigue crack propagation in quasi-brittle materials
A. Baktheer, E. MartÃnez-Pañeda, F. Aldakheel
The phase field method has gathered significant attention in the past decade due to its versatile applications in engineering contexts, including fatigue crack propagation modeling…