research
∙
01/26/2023
The multifaceted nature of uncertainty in structure-property linkage with crystal plasticity finite element model
Uncertainty quantification (UQ) plays a critical role in verifying and v...
share
research
∙
10/07/2020
Solving stochastic inverse problems for property-structure linkages using data-consistent inversion and machine learning
Determining process-structure-property linkages is one of the key object...
research
∙
05/30/2020
Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloys
We present a scale-bridging approach based on a multi-fidelity (MF) mach...
research
∙
04/24/2020
An active learning high-throughput microstructure calibration framework for solving inverse structure-process problems in materials informatics
Determining a process-structure-property relationship is the holy grail ...
research
∙
03/30/2020
Multiscale stochastic reduced-order model for uncertainty propagation using Fokker-Planck equation with microstructure evolution applications
Uncertainty involved in computational materials modeling needs to be qua...
research
∙
03/20/2020
