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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

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Spelling suggestions: "subject:"sattelpunkte"" "subject:"sattelpunkt""

1

Fast simulation of (nearly) incompressible nonlinear elastic material at large strain via adaptive mixed FEM

Balg, Martina, Meyer, Arnd 19 October 2012 (has links) (PDF)
The main focus of this work lies in the simulation of the deformation of mechanical components which consist of nonlinear elastic, incompressible material and that are subject to large deformations. Starting from a nonlinear formulation one can derive a discrete problem by using linearisation techniques and an adaptive mixed finite element method. This turns out to be a saddle point problem that can be solved via a Bramble-Pasciak conjugate gradient method. With some modifications the simulation can be improved.
Sattelpunktproblem
große Deformation
gemischte Finite-Elemente-Methode
nonlinear elasticity
large strain
adaptivity
mixed finite element method
saddle point problem
ddc:518
Inkompressibilität
Nichtlineare Elastizitätstheorie
Adaptives Verfahren
2

Fast simulation of (nearly) incompressible nonlinear elastic material at large strain via adaptive mixed FEM

Balg, Martina, Meyer, Arnd 19 October 2012 (has links)
The main focus of this work lies in the simulation of the deformation of mechanical components which consist of nonlinear elastic, incompressible material and that are subject to large deformations. Starting from a nonlinear formulation one can derive a discrete problem by using linearisation techniques and an adaptive mixed finite element method. This turns out to be a saddle point problem that can be solved via a Bramble-Pasciak conjugate gradient method. With some modifications the simulation can be improved.:1. Introduction 2. Basics 3. Mixed variational formulation 4. Solution method 5. Error estimation 6. LBB conditions 7. Improvement suggestions
info:eu-repo/classification/ddc/518
ddc:518

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