3 papers
cond-mat.mtrl-sci2024
Universal Design Methodology for Printable Microstructural Materials via a New Deep Generative Learning Model: Application to a Piezocomposite
Mohammad Saber Hashemi, Khiem Nguyen, Levi Kirby +2
We devised a general heterogeneous microstructural design methodology applied to a specific material system, elasto-electro-active piezoelectric ceramic embedded plastics, which ha…
eess.IV2023
Predicting Bone Degradation Using Vision Transformer and Synthetic Cellular Microstructures Dataset
Mohammad Saber Hashemi, Azadeh Sheidaei
Bone degradation, especially for astronauts in microgravity conditions, is crucial for space exploration missions since the lower applied external forces accelerate the diminution…
cond-mat.mtrl-sci2023
A peridynamic-informed deep learning model for brittle damage prediction
Roozbeh Eghbalpoor, Azadeh Sheidaei
In this study, a novel approach that combines the principles of peridynamic (PD) theory with PINN is presented to predict quasi-static damage and crack propagation in brittle mater…