A mechanics‐informed artificial neural network approach in data‐driven constitutive modeling-Reference-Cited by-同舟云学术

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A mechanics‐informed artificial neural network approach in data‐driven constitutive modeling

Published:2022-03-07 Issue:12 Volume:123 Page:2738-2759
ISSN:0029-5981
Container-title:International Journal for Numerical Methods in Engineering
language:en
Short-container-title:Numerical Meth Engineering

Author:

As'ad Faisal¹^ORCID,Avery Philip¹^ORCID,Farhat Charbel¹²³^ORCID

Affiliation:

1. Department of Aeronautics and Astronautics Stanford University Stanford California USA

2. Institute for Computational and Mathematical Engineering Stanford University Stanford California USA

3. Department of Mechanical Engineering Stanford University Stanford California USA

Funder

Air Force Office of Scientific Research

National Aeronautics and Space Administration

National Science Foundation of Sri Lanka

Publisher

Wiley

Subject

Applied Mathematics,General Engineering,Numerical Analysis

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nme.6957

Reference43 articles.

1. An empirical statistical constitutive relationship for rock joint shearing considering scale effect

2. A phenomenological constitutive model for rubberlike materials and its numerical applications

3. Microstructurally-based constitutive modelling of the skin – Linking intrinsic ageing to microstructural parameters

4. As'adF AveryP FarhatC.A mechanics‐informed artificial neural network approach in data‐driven constitutive modeling. Proceedings of the AIAA Scitech 2022 Forum; 2022:0100; AIAA.

5. Knowledge‐Based Modeling of Material Behavior with Neural Networks

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