CNN-based prediction of microstructure-derived random property fields of composite materials

Gavallas, Panagiotis; Stefanou, George; Savvas, Dimitrios; Mattrand, Cécile; Bourinet, Jean-Marc

doi:10.1016/j.cma.2024.117207

Computer Methods in Applied Mechanics and Engineering

2024

DOI: 10.1016/j.cma.2024.117207

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CNN-based prediction of microstructure-derived random property fields of composite materials

Panagiotis Gavallas,

George Stefanou,

Dimitrios Savvas

et al.

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A Review of Recent Advances in Surrogate Models for Uncertainty Quantification of High-Dimensional Engineering Applications

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Ilchi Ghazaan

2025

Computer Methods in Applied Mechanics and Engineering

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A Review of Recent Advances in Surrogate Models for Uncertainty Quantification of High-Dimensional Engineering Applications

Azarhoosh,

Ilchi Ghazaan

2025

Computer Methods in Applied Mechanics and Engineering

View full text Add to dashboard Cite

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CNN-based prediction of microstructure-derived random property fields of composite materials

Cited by 1 publication

References 32 publications

A Review of Recent Advances in Surrogate Models for Uncertainty Quantification of High-Dimensional Engineering Applications

A Review of Recent Advances in Surrogate Models for Uncertainty Quantification of High-Dimensional Engineering Applications

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