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Geometrically Unfitted Finite Element Methods and Applications

Proceedings of the UCL Workshop 2016

  • Conference proceedings
  • © 2017

Overview

  • Provides a snapshot of the latest research in unfitted finite element methods and extended finite element methods
  • Presents core material, such as unfitted FEM for elasticity and augmented Lagrangian techniques for contact problems
  • Explores applications of the presented methods to problems in continuum mechanics

Part of the book series: Lecture Notes in Computational Science and Engineering (LNCSE, volume 121)

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Table of contents (11 papers)

Keywords

About this book

This book provides a snapshot of the state of the art of the rapidly evolving field of integration of geometric data in finite element computations.

The contributions to this volume, based on research presented at the UCL workshop on the topic in January 2016, include three review papers on core topics such as fictitious domain methods for elasticity, trace finite element methods for partial differential equations defined on surfaces, and Nitsche’s method for contact problems. Five chapters present original research articles on related theoretical topics, including Lagrange multiplier methods, interface problems, bulk-surface coupling, and approximation of partial differential equations on moving domains. Finally, two chapters discuss advanced applications such as crack propagation or flow in fractured poroelastic media.

This is the first volume that provides a comprehensive overview of the field of unfitted finite element methods, including recent techniques such as cutFEM, traceFEM, ghost penalty, and augmented Lagrangian techniques. It is aimed at researchers in applied mathematics, scientific computing or computational engineering.

Editors and Affiliations

  • Faculté des Sciences, de la Technologie et de la Communication, Université du Luxembourg, Luxembourg

    Stéphane P. A. Bordas

  • Department of Mathematics, University College London, United Kingdom

    Erik Burman

  • Department of Mathematics and Mathematical Statistics, Umeå University, Sweden

    Mats G. Larson

  • Department of Mathematics, University of Houston, USA

    Maxim A. Olshanskii

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