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20222026
most citedPhysically recurrent neural networks for path-dependent heterogeneous materials: embedding constitutive models in a data-driven surrogate

81 citations · 86 across the 5 of their papers we have counts for

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Showing 2024Show all

2 papers · 1 filter

math.NA2024

Physically Recurrent Neural Networks for Computational Homogenization of Composite Materials with Microscale Debonding

N. Kovács, M. A. Maia, I. B. C. M. Rocha +3

The growing use of composite materials in engineering applications has accelerated the demand for computational methods to accurately predict their complex behavior. Multiscale mod…

cond-mat.mtrl-sci2024★ 1 cited

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…