5 citations · 6 across the 2 of their papers we have counts for
7 papers
Sensitivity of void mediated failure to geometric design features of porous metals
Gregory H. Teichert, Mohammad Khalil, Coleman Alleman +2
Material produced by current metal additive manufacturing processes is susceptible to variable performance due to imprecise control of internal porosity, surface roughness, and con…
Tensor Basis Gaussian Process Models of Hyperelastic Materials
Ari Frankel, Reese Jones, Laura Swiler
In this work, we develop Gaussian process regression (GPR) models of hyperelastic material behavior. First, we consider the direct approach of modeling the components of the Cauchy…
Prediction of the evolution of the stress field of polycrystals undergoing elastic-plastic deformation with a hybrid neural network model
Ari Frankel, Kousuke Tachida, Reese Jones
Crystal plasticity theory is often employed to predict the mesoscopic states of polycrystalline metals, and is well-known to be costly to simulate. Using a neural network with conv…
Predicting the mechanical response of oligocrystals with deep learning
Ari L. Frankel, Reese E. Jones, Coleman Alleman +1
In this work we employ data-driven homogenization approaches to predict the particular mechanical evolution of polycrystalline aggregates with tens of individual crystals. In these…
Machine learning models of plastic flow based on representation theory
Reese E. Jones, Jeremy A. Templeton, Clay M. Sanders +1
We use machine learning (ML) to infer stress and plastic flow rules using data from repre- sentative polycrystalline simulations. In particular, we use so-called deep (multilayer)…
Bayesian Modeling of Inconsistent Plastic Response due to Material Variability
Francesco Rizzi, Mohammad Khalil, Reese E. Jones +3
The advent of fabrication techniques such as additive manufacturing has focused attention on the considerable variability of material response due to defects and other microstructu…