Metadata only
Datum
2021Typ
- Journal Article
Abstract
We consider scalar-valued shape functionals on sets of shapes which are small perturbations of a reference shape. The shapes are described by parameterizations and their closeness is induced by a Hilbert space structure on the parameter domain. We justify a heuristic for finding the best low-dimensional parameter subspace with respect to uniformly approximating a given shape functional. We also propose an adaptive algorithm for achieving a prescribed accuracy when representing the shape functional with a small number of shape parameters. Mehr anzeigen
Publikationsstatus
publishedExterne Links
Zeitschrift / Serie
Numerical Functional Analysis and OptimizationBand
Seiten / Artikelnummer
Verlag
Taylor & FrancisThema
Model reduction; Shape calculus; Shape gradient; shape Hessian; Low-rank approximation; power iterationOrganisationseinheit
03632 - Hiptmair, Ralf / Hiptmair, Ralf