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Neural networks in computational damage mechanics

Authors
Publisher
Elsevier Ltd
Identifiers
DOI: 10.1016/b978-008044046-0.50105-6
Disciplines
  • Computer Science

Abstract

Publisher Summary This chapter presents the assessment of neural network performance with respect to the choice of basis functions used to compute numerical training patterns. Within this framework of damage and localization material modeling, soft computing, specifically neural networks, is used to alleviate the computational cost associated to the return mapping and/or continuation schemes that are needed to solve the nonlinear governing equations and to detect regions of localization onset.

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