Novel Geometric Deep Learning Surrogate Framework for Non-Linear Finite Element Simulations

Deshpande, Saurabh; Lengiewicz, Jakub; Bordas, Stéphane

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Poster (Scientific congresses, symposiums and conference proceedings)

Novel Geometric Deep Learning Surrogate Framework for Non-Linear Finite Element Simulations

Deshpande, Saurabh; Lengiewicz, Jakub; Bordas, Stéphane

2023 • The Platform for Advanced Scientific Computing (PASC) Conference 2023

Peer reviewed

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https://hdl.handle.net/10993/55643

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Research center :

ULHPC - University of Luxembourg: High Performance Computing

Disciplines :

Engineering, computing & technology: Multidisciplinary, general & others

Author, co-author :

Deshpande, Saurabh ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)

Lengiewicz, Jakub ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)

Bordas, Stéphane ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)

External co-authors :

yes

Language :

English

Title :

Novel Geometric Deep Learning Surrogate Framework for Non-Linear Finite Element Simulations

Publication date :

27 June 2023

Event name :

The Platform for Advanced Scientific Computing (PASC) Conference 2023

Event date :

26-06-2023 to 28-06-2023

Peer reviewed :

Peer reviewed

Focus Area :

Computational Sciences

European Projects :

H2020 - 764644 - RAINBOW - Rapid Biomechanics Simulation for Personalized Clinical Design

Name of the research project :

R-AGR-3325 - H2020-MSCA-ITN-2017-764644-RAINBOW (01/04/2018 - 31/03/2023) - BORDAS Stéphane

Funders :

CE - Commission Européenne [BE]
Union Européenne [BE]

Available on ORBilu :

since 20 July 2023

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