3 papers
cond-mat.mtrl-sci2024
Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response
Ravi Patel, Cosmin Safta, Reese E. Jones
Composite materials with different microstructural material symmetries are common in engineering applications where grain structure, alloying and particle/fiber packing are optimiz…
cond-mat.mtrl-sci2022
Bayesian calibration of interatomic potentials for binary alloys
Arun Hegde, Elan Weiss, Wolfgang Windl +2
Developing reliable interatomic potential models with quantified predictive accuracy is crucial for atomistic simulations. Commonly used potentials, such as those constructed throu…
stat.CO2021
Generalized Transitional Markov Chain Monte Carlo Sampling Technique for Bayesian Inversion
Han Lu, Mohammad Khalil, Thomas Catanach +5
In the context of Bayesian inversion for scientific and engineering modeling, Markov chain Monte Carlo sampling strategies are the benchmark due to their flexibility and robustness…