Unsupervised machine learning classification for accelerating FE<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si58.svg" display="inline" id="d1e1310"><mml:msup><mml:mrow/><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math> multiscale fracture simulations-Reference-Cited by-同舟云学术

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Unsupervised machine learning classification for accelerating FE2 multiscale fracture simulations

Published:2024-12 Issue: Volume:432 Page:117278
ISSN:0045-7825
Container-title:Computer Methods in Applied Mechanics and Engineering
language:en
Short-container-title:Computer Methods in Applied Mechanics and Engineering

Author:

Chaouch Souhail,Yvonnet Julien

Funder

Bosch Research Foundation

Publisher

Elsevier BV

Reference69 articles.

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2. Prediction of the mechanical behavior of nonlinear heterogeneous systems by multi-level finite element modeling;Smit;Comput. Methods Appl. Mech. Engrg.,1998

3. Computational homogenization analysis in finite plasticity simulation of texture development in polycrystalline materials;Miehe;Comput. Methods Appl. Mech. Engrg.,1999

4. Multiscale FE2 elastoviscoplastic analysis of composite structures;Feyel;Comput. Mater. Sci.,1999

5. FE2 multiscale approach for modelling the elastoviscoplastic behaviour of long fibre SiC/Ti composite materials;Feyel;Comput. Methods Appl. Mech. Engrg.,2000

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