About: Shape optimization via a levelset and a Gauss-Newton method

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Attributs	Valeurs
type	work Article
Is Part Of	http://hub.abes.fr/edp/periodical/cocv/2019/volume_25/issue_2019/w
Subject	Newton-type methods Methods involving duality Optimization of shapes other than minimal surfaces Compliance or weight optimization Optimization of other properties Geometrical methods level-set method second order method Shape optimization shape derivative
Title	Shape optimization via a levelset and a Gauss-Newton method
Date	2019-01-01(xsd:dateTime)
has manifestation of work	http://hub.abes.fr/edp/periodical/cocv/2019/volume_25/issue_2019/cocv160095/m/print http://hub.abes.fr/edp/periodical/cocv/2019/volume_25/issue_2019/cocv160095/m/web
related by	http://hub.abes.fr/edp/periodical/cocv/2019/volume_25/issue_2019/cocv160095/authorship/1 http://hub.abes.fr/edp/periodical/cocv/2019/volume_25/issue_2019/cocv160095/authorship/2
Author	de Gournay, Frédéric Fehrenbach, Jérôme
Abstract	In the context of shape optimization via level-set methods, we propose a general framework for a Gauss-Newton method to optimize quadratic functionals. Our approach provides a natural extension of the shape derivative as a vector field defined in the whole working domain. We implement and discuss this method in two cases: first a least-square error minimization reminiscent of the Electrical Impedance Tomography problem, and second the compliance problem with volume constraints.
article type	research-article
publisher identifier	cocv160095
Date Copyrighted	2019-01-01(xsd:dateTime)
Rights	© EDP Sciences, SMAI 2019
Rights Holder	EDP Sciences, SMAI
is part of this journal	ESAIM: Control, Optimisation and Calculus of Variations
is primary topic of	http://hub.abes.fr/edp/periodical/cocv/2019/volume_25/issue_2019/cocv160095/w/record

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