F. P. van der Meer

Orcid: 0000-0002-6691-1259

Affiliations:
  • Delft University of Technology, Faculty of Civil Engineering and Geosciences, The Netherlands


According to our database1, F. P. van der Meer authored at least 16 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of six.
  • Erdős number3 of five.

Timeline

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Bibliography

2025
Mixing Data-Driven and Physics-Based Constitutive Models using Uncertainty-Driven Phase Fields.
CoRR, April, 2025

A viscoplasticity model with an invariant-based non-Newtonian flow rule for unidirectional thermoplastic composites.
CoRR, April, 2025

Uncertainty Quantification in Multiscale Modeling of Polymer Composite Materials Using Physically Recurrent Neural Networks.
CoRR, April, 2025

Effects of Interpolation Error and Bias on the Random Mesh Finite Element Method for Inverse Problems.
CoRR, April, 2025

Surrogate-based multiscale analysis of experiments on thermoplastic composites under off-axis loading.
CoRR, January, 2025

2024
A Bayesian approach to modeling finite element discretization error.
Stat. Comput., October, 2024

Physically Recurrent Neural Networks for Computational Homogenization of Composite Materials with Microscale Debonding.
CoRR, 2024

Physically recurrent neural network for rate and path-dependent heterogeneous materials in a finite strain framework.
CoRR, 2024

Modeling of progressive high-cycle fatigue in composite laminates accounting for local stress ratios.
CoRR, 2024

A Microstructure-based Graph Neural Network for Accelerating Multiscale Simulations.
CoRR, 2024

2023
A numerical framework for simulating progressive failure in composite laminates under high-cycle fatigue loading.
CoRR, 2023

Machine learning of evolving physics-based material models for multiscale solid mechanics.
CoRR, 2023

2022
Physically recurrent neural networks for path-dependent heterogeneous materials: embedding constitutive models in a data-driven surrogate.
CoRR, 2022

Data presented in the paper: "Microscale modeling of rate-dependent failure in thermoplastic composites under off-axis loading".
Dataset, 2022

2021
Parallel Computing with the Thick Level Set Method.
SIAM J. Sci. Comput., 2021

On-the-fly construction of surrogate constitutive models for concurrent multiscale mechanical analysis through probabilistic machine learning.
J. Comput. Phys. X, 2021


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