An encapsulating non-local framework for data-driven multiscale simulations of composite material failure

Anglade, Cyrielle; Wu, Ling; Lemoine, Guerric; Noels, Ludovic

doi:10.1016/j.euromechsol.2026.106428

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An encapsulating non-local framework for data-driven multiscale simulations of composite material failure

Anglade, Cyrielle; Wu, Ling; Lemoine, Guerric et al.

2027 • In European Journal of Mechanics. A, Solids, (122), p. 106428

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10.1016/j.euromechsol.2026.106428

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his project has received funding from the European Union’s Horizon Europe Framework Programme under grant agreement No. 101056682 for the project “DIgital DEsign strategies to certify and mAnufacture Robust cOmposite sTructures (DIDEAROT)”. The contents of this publication are the sole responsibility of ULiege and do not necessarily reflect the opinion of the European Union. Neither the European Union nor the granting authority can be held responsible for them.

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Keywords :

Multiscale; Recurrent neural network; Non-local damage; Data-driven; Composites

Abstract :

[en] Multiscale simulations of composite materials are often unpractical for complex non-linear material responses, in particular because of their inherent computational cost. Data-driven approaches make the development of surrogates of complex heterogeneous material responses possible. Such surrogates are trained from a synthetic data-set built using off-line simulations conducted on a micro-scale Boundary Value Problem (BVP). Once trained, they can substitute a micro-scale BVP resolution inherent to a multiscale simulation reducing the online computational time by several orders of magnitude. Neural-networks (NNWs) in general, and recurrent neural-networks in particular for history-dependent problems, are particularly efficient surrogates. However the extension to failure analyses of data-driven approaches poses several challenges to account for the strain softening of the homgenised micro-scale response. On the one hand, the response of the micro-scale BVPs becomes dependent on the size of the volume element they are built on, preventing exploiting the homogenised micro-scale response in a multiscale setting. On the other hand, the loss of ellipticity at the macro-scale makes the solution (macro-)mesh-size dependent. These limitations are circumvented in this work by building a homogenised non-local damage material law fed by NNW predictions of the underlying micro-scale BVP response. This yields to a regularised expression of the predicted homogenised response controlled by characteristic lengths. In particular, the characteristic lengths of the resulting encapsulating non-local framework are determined so that the fracture energy of the homogenised material is consistent with the micro-scale response. The method is applied on Unidirectional (UD) composites by training the surrogate using Volume Element simulations for which the matrix exhibits a strain softening. Transverse and shear loading conditions are then applied on coupons, simulated with the developed non-local surrogate-based multiscale approach, and compared to direct numerical simulations (DNS), showing good accuracy while reducing the system size and computational cost.

Research Center/Unit :

A&M - Aérospatiale et Mécanique - ULiège

Disciplines :

Mechanical engineering

Author, co-author :

Anglade, Cyrielle ; Université de Liège - ULiège > Aérospatiale et Mécanique (A&M)

Wu, Ling ; Université de Liège - ULiège > Aérospatiale et Mécanique (A&M)

Lemoine, Guerric

Noels, Ludovic ; Université de Liège - ULiège > Aérospatiale et Mécanique (A&M)

Language :

English

Title :

An encapsulating non-local framework for data-driven multiscale simulations of composite material failure

Publication date :

March 2027

Journal title :

European Journal of Mechanics. A, Solids

ISSN :

0997-7538

Publisher :

Elsevier BV

Issue :

122

Pages :

106428

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://api.elsevier.com/content/article/PII:S0997753826004146?httpAccept=text/xml

European Projects :

HE - 101056682 - DIDEAROT - Digital Design strategies to certify and mAnufacture Robust cOmposite sTructures 

Name of the research project :

DIDEAROT - Digital Design strategies to certify and mAnufacture Robust cOmposite sTructures 

Funders :

Horizon Europe
European Union

Funding number :

101056682

Funding text :

Available on ORBi :

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