26 citations · 48 across the 11 of their papers we have counts for
4 papers · 1 filter
Investigating Deep Learning Model Calibration for Classification Problems in Mechanics
Saeed Mohammadzadeh, Peerasait Prachaseree, Emma Lejeune
Recently, there has been a growing interest in applying machine learning methods to problems in engineering mechanics. In particular, there has been significant interest in applyin…
Enhancing Mechanical Metamodels with a Generative Model-Based Augmented Training Dataset
Hiba Kobeissi, Saeed Mohammadzadeh, Emma Lejeune
Modeling biological soft tissue is complex in part due to material heterogeneity. Microstructural patterns, which play a major role in defining the mechanical behavior of these tis…
Learning Mechanically Driven Emergent Behavior with Message Passing Neural Networks
Peerasait Prachaseree, Emma Lejeune
From designing architected materials to connecting mechanical behavior across scales, computational modeling is a critical tool in solid mechanics. Recently, there has been a growi…
Predicting Mechanically Driven Full-Field Quantities of Interest with Deep Learning-Based Metamodels
S. Mohammadzadeh, E. Lejeune
Using simulation to predict the mechanical behavior of heterogeneous materials has applications ranging from topology optimization to multi-scale structural analysis. However, full…