Machine Learning of Dislocation-Induced Stress Fields and Interaction Forces

In discrete dislocation dynamics (DDD) simulations dislocation-induced stress fields and dislocation–dislocation interaction forces are typically evaluated using analytically described multiparameter continuous functions. The universal approximation theory guarantees the approximation of such functi...

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Bibliographic Details
Published in:JOM (1989) Vol. 72; no. 12; pp. 4380 - 4392
Main Authors: Rafiei, Mohammad H., Gu, Yejun, El-Awady, Jaafar A.
Format: Journal Article
Language:English
Published: New York Springer US 01.12.2020
Springer Nature B.V
Subjects:
Approximation
Artificial neural networks
Augmenting Physics-based Models in ICME with Machine Learning and Uncertainty Quantification
Chemistry/Food Science
Continuity (mathematics)
Earth Sciences
Engineering
Environment
Exact solutions
Machine learning
Neural networks
Physics
Simulation
Stress distribution
ISSN:1047-4838, 1543-1851
Online Access:Get full text
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Summary:In discrete dislocation dynamics (DDD) simulations dislocation-induced stress fields and dislocation–dislocation interaction forces are typically evaluated using analytically described multiparameter continuous functions. The universal approximation theory guarantees the approximation of such functions by some machine learning (ML) techniques, which in turn can potentially help to accelerate DDD simulations. However, accurate machine approximation is as crucial as its acceleration. Here, we demonstrate the feasibility of utilizing deep neural networks to predict dislocation-induced stress fields and dislocation–dislocation interaction forces. We also show that the trained network produces estimates that are in very good agreement with analytical solutions. This was only plausible by generating an enriched data repository to avoid bias in the training data. This work opens the door to further development of more optimized ML architectures that could lead to a more computationally efficient, yet accurate, approach to replace the generally inefficient analytical calculations of dislocation–dislocation interaction forces in DDD simulations.
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ISSN:1047-4838
1543-1851
DOI:10.1007/s11837-020-04389-w