1 citations · 2 across the 3 of their papers we have counts for
3 papers
Physically recurrent neural network for rate and path-dependent heterogeneous materials in a finite strain framework
M. A. Maia, I. B. C. M. Rocha, D. Kovačević +1
In this work, a hybrid physics-based data-driven surrogate model for the microscale analysis of heterogeneous material is investigated. The proposed model benefits from the physics…
A Microstructure-based Graph Neural Network for Accelerating Multiscale Simulations
J. Storm, I. B. C. M. Rocha, F. P. van der Meer
Simulating the mechanical response of advanced materials can be done more accurately using concurrent multiscale models than with single-scale simulations. However, the computation…
Machine learning of evolving physics-based material models for multiscale solid mechanics
I. B. C. M. Rocha, P. Kerfriden, F. P. van der Meer
In this work we present a hybrid physics-based and data-driven learning approach to construct surrogate models for concurrent multiscale simulations of complex material behavior. W…