Iuri B. C. M. Rocha

According to our database, Iuri B. C. M. Rocha authored at least 14 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of six.
• Erdős number of five.

2025

The Bayesian Finite Element Method in Inverse Problems: a Critical Comparison between Probabilistic Models for Discretization Error.

Anne Poot, Iuri Rocha, Pierre Kerfriden, Frans van der Meeer

CoRR, June, 2025

Mixing Data-Driven and Physics-Based Constitutive Models using Uncertainty-Driven Phase Fields.

J. Storm, W. Sun, Iuri B. C. M. Rocha, F. P. van der Meer

CoRR, April, 2025

Uncertainty Quantification in Multiscale Modeling of Polymer Composite Materials Using Physically Recurrent Neural Networks.

N. Kovács, Iuri B. C. M. Rocha, F. P. van der Meer, C. Furtado, Pedro P. Camanho

CoRR, April, 2025

Effects of Interpolation Error and Bias on the Random Mesh Finite Element Method for Inverse Problems.

Anne Poot, Iuri Rocha, Pierre Kerfriden, Frans van der Meer

CoRR, April, 2025

Multiscale Analysis of Woven Composites Using Hierarchical Physically Recurrent Neural Networks.

Ehsan Ghane, Marina A. Maia, Iuri B. C. M. Rocha, Martin Fagerström, Mohsen Mirakhalaf

CoRR, March, 2025

Surrogate-based multiscale analysis of experiments on thermoplastic composites under off-axis loading.

Marina A. Maia, Iuri B. C. M. Rocha, Dragan Kovacevic, F. P. van der Meer

CoRR, January, 2025

2024

A Bayesian approach to modeling finite element discretization error.

Anne Poot, Pierre Kerfriden, Iuri Rocha, Frans Paul van der Meer

Stat. Comput., October, 2024

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

N. Kovács, Marina A. Maia, Iuri B. C. M. Rocha, C. Furtado, Pedro P. Camanho, F. P. van der Meer

CoRR, 2024

Physically recurrent neural network for rate and path-dependent heterogeneous materials in a finite strain framework.

Marina A. Maia, Iuri B. C. M. Rocha, Dragan Kovacevic, F. P. van der Meer

CoRR, 2024

A Microstructure-based Graph Neural Network for Accelerating Multiscale Simulations.

J. Storm, Iuri B. C. M. Rocha, F. P. van der Meer

CoRR, 2024

2023

A Bayesian Approach to Modeling Finite Element Discretization Error.

Anne Poot, Pierre Kerfriden, Iuri Rocha, rans Paul van der Meer

CoRR, 2023

Machine learning of evolving physics-based material models for multiscale solid mechanics.

Iuri B. C. M. Rocha, Pierre Kerfriden, F. P. van der Meer

CoRR, 2023

2022

Physically recurrent neural networks for path-dependent heterogeneous materials: embedding constitutive models in a data-driven surrogate.

Marina A. Maia, Iuri B. C. M. Rocha, Pierre Kerfriden, F. P. van der Meer

CoRR, 2022

2021

On-the-fly construction of surrogate constitutive models for concurrent multiscale mechanical analysis through probabilistic machine learning.

Iuri B. C. M. Rocha, Pierre Kerfriden, F. P. van der Meer

J. Comput. Phys. X, 2021