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On gradient‐based optimization strategies for inverse problems in metal forming
Author(s) -
Landkamer P.,
Söhngen B.,
Steinmann P.,
Willner K.
Publication year - 2017
Publication title -
gamm‐mitteilungen
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.239
H-Index - 18
eISSN - 1522-2608
pISSN - 0936-7195
DOI - 10.1002/gamm.201710004
Subject(s) - subroutine , inverse problem , inverse , mathematical optimization , context (archaeology) , minification , finite element method , computer science , least squares function approximation , optimization problem , algorithm , mathematics , engineering , structural engineering , mathematical analysis , estimator , biology , operating system , paleontology , statistics , geometry
In the context of metal forming, optimization issues typically lead to inverse problems with a least‐squares minimization as the objective. Due to the nonlinearities in forming simulations, iterative optimization approaches have to be considered. Gradient‐based solution strategies for two inverse problems are proposed and compared to each other. Firstly, the identification of elasto‐plastic material parameters is regarded. Secondly, a recently developed approach for the determination of an optimal workpiece design is investigated. As a special feature, both approaches can be coupled in a non‐invasive fashion to arbitrary external finite element software via subroutines.