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Multiscale simulation of polymeric fluids using the sparse grid combination technique

dc.contributor.authorRüttgers, Alexander
dc.contributor.authorGriebel, Michael
dc.date.accessioned2024-08-27T10:03:58Z
dc.date.available2024-08-27T10:03:58Z
dc.date.issued10.2017
dc.identifier.urihttps://hdl.handle.net/20.500.11811/11978
dc.description.abstractWe present a computationally efficient sparse grid approach to allow for multiscale simulations of non-Newtonian polymeric fluids. Multiscale approaches for polymeric fluids often involve model equations of high dimensionality. A conventional numerical treatment of such equations leads to computing times in the order of months even on massively parallel computers.
For a reduction of this enormous complexity, we propose the sparse grid combination technique. Compared to classical full grid approaches, the combination technique strongly reduces the computational complexity of a numerical scheme but only slightly decreases its accuracy.
Here, we use the combination technique in a general formulation that balances not only different discretization errors but also considers the accuracy of the mathematical model. For an optimal weighting of these different problem dimensions, we employ a dimension-adaptive refinement strategy. We finally verify substantial cost reductions of our approach for simulations of non-Newtonian Couette and extensional flow problems.
en
dc.format.extent25
dc.language.isoeng
dc.relation.ispartofseriesINS Preprints ; 1623
dc.rightsIn Copyright
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectsparse grids
dc.subjectcombination technique
dc.subjectdimension-adaptivity
dc.subjectmultiscale simulation
dc.subjectBrownian configuration fields
dc.subjectmulti-bead spring-chains
dc.subject.ddc510 Mathematik
dc.subject.ddc518 Numerische Analysis
dc.titleMultiscale simulation of polymeric fluids using the sparse grid combination technique
dc.typePreprint
dc.publisher.nameInstitut für Numerische Simulation (INS)
dc.publisher.locationBonn
dc.rights.accessRightsopenAccess
dc.relation.doihttps://doi.org/10.1016/j.amc.2017.04.025
ulbbn.pubtypeZweitveröffentlichung
dc.versionupdatedVersion
dcterms.bibliographicCitation.urlhttps://ins.uni-bonn.de/publication/preprints


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