Optimization of piecewise smooth shapes under uncertainty using the example of Navier--Stokes flow

dc.bibliographicCitation.seriesTitleWIAS Preprintseng
dc.bibliographicCitation.volume3037
dc.contributor.authorGeiersbach, Caroline
dc.contributor.authorSuchan, Tim
dc.contributor.authorWelker, Kathrin
dc.date.accessioned2026-03-26T09:05:40Z
dc.date.available2026-03-26T09:05:40Z
dc.date.issued2023
dc.description.abstractWe investigate a complex system involving multiple shapes to be optimized in a domain, taking into account geometric constraints on the shapes and uncertainty appearing in the physics. We connect the differential geometry of product shape manifolds with multi-shape calculus, which provides a novel framework for the handling of piecewise smooth shapes. This multi-shape calculus is applied to a shape optimization problem where shapes serve as obstacles in a system governed by steady state incompressible Navier--Stokes flow. Numerical experiments use our recently developed stochastic augmented Lagrangian method and we investigate the choice of algorithmic parameters using the example of this application.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/33665
dc.identifier.urihttps://doi.org/10.34657/32733
dc.language.isoeng
dc.publisherBerlin : Weierstraß-Institut für Angewandte Analysis und Stochastik
dc.relation.doihttps://doi.org/10.20347/WIAS.PREPRINT.3037
dc.relation.essn2198-5855
dc.relation.issn0946-8633
dc.rights.licenseCC BY 4.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc510
dc.subject.otherShape optimizationeng
dc.subject.otherproduct manifoldeng
dc.subject.otheraugmented Lagrangianeng
dc.subject.otherstochastic optimizationeng
dc.subject.otheruncertaintieseng
dc.titleOptimization of piecewise smooth shapes under uncertainty using the example of Navier--Stokes floweng
dc.typeReport
tib.accessRightsopenAccess
wgl.contributorWIAS
wgl.subjectMathematik
wgl.typeReport / Forschungsbericht / Arbeitspapier

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
wias_preprints_3037.pdf
Size:
1.87 MB
Format:
Adobe Portable Document Format
Description: