From the 1 of 6 linked papers with an AI index.
6 papers
Materials Behavior as Mechanism Ensembles: A Probabilistic Framework for Emergent Behaviors
Brad L. Boyce, Mitchell A. Wood, Krishna Garikipati +16
The paper proposes a probabilistic framework that treats material behavior as an ensemble of competing mechanisms, using fatigue crack propagation as an example to show how mechani…
Fast Multitask Gaussian Process Regression
Aleksei G. Sorokin, Pieterjan Robbe, Fred J. Hickernell
Gaussian process (GP) regression is a powerful probabilistic modeling technique with built-in uncertainty quantification. When one has access to multiple correlated simulations (ta…
Towards Spatio-Temporal Extrapolation of Phase-Field Simulations with Convolution-Only Neural Networks
Christophe Bonneville, Nathan Bieberdorf, Pieterjan Robbe +4
Phase-field simulations of liquid metal dealloying (LMD) can capture complex microstructural evolutions but can be prohibitively expensive for large domains and long time horizons.…
Fast Bayesian Multilevel Quasi-Monte Carlo
Aleksei G. Sorokin, Pieterjan Robbe, Gianluca Geraci +2
Existing multilevel quasi-Monte Carlo (MLQMC) methods often rely on multiple independent randomizations of a low-discrepancy (LD) sequence to estimate statistical errors on each le…
Extrapolating Phase-Field Simulations in Space and Time with Purely Convolutional Architectures
Christophe Bonneville, Nathan Bieberdorf, Pieterjan Robbe +4
Phase-field models of liquid metal dealloying (LMD) can resolve rich microstructural dynamics but become intractable for large domains or long time horizons. We present a condition…
A Comparison of Surrogate Constitutive Models for Viscoplastic Creep Simulation of HT-9 Steel
Pieterjan Robbe, Andre Ruybalid, Arun Hegde +4
Mechanistic microstructure-informed constitutive models for the mechanical response of polycrystals are a cornerstone of computational materials science. However, as these models b…