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Topology optimization with implicit functions and regularization
Author(s) -
Belytschko T.,
Xiao S. P.,
Parimi C.
Publication year - 2003
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.824
Subject(s) - heaviside step function , topology optimization , regularization (linguistics) , mathematics , topology (electrical circuits) , function (biology) , mathematical optimization , finite element method , computer science , mathematical analysis , physics , combinatorics , artificial intelligence , evolutionary biology , biology , thermodynamics
Topology optimization is formulated in terms of the nodal variables that control an implicit function description of the shape. The implicit function is constrained by upper and lower bounds, so that only a band of nodal variables needs to be considered in each step of the optimization. The weak form of the equilibrium equation is expressed as a Heaviside function of the implicit function; the Heaviside function is regularized to permit the evaluation of sensitivities. We show that the method is a dual of the Bends–Kikuchi method. The method is applied both to problems of optimizing single material and multi‐material configurations; the latter is made possible by enrichment functions based on the extended finite element method that enable discontinuous derivatives to be accurately treated within an element. The method is remarkably robust and we found no instances of checkerboarding. The method handles topological merging and separation without any apparent difficulties. Copyright © 2003 John Wiley & Sons, Ltd.