Weakly Enforced Boundary Conditions for the NURBS-Based Finite Cell Method

Ruess, M. , Bazilevs, Y., Schillinger, D., Zander, N. and Rank, E. (2012) Weakly Enforced Boundary Conditions for the NURBS-Based Finite Cell Method. In: European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2012), Vienna, Austria, 10-14 Sept 2012, pp. 1-16. ISBN 9783950248197

Abstract

In this paper, we present a variationally consistent formulation for the weak enforcement of essential boundary conditions as an extension to the finite cell method, a fictitious domain method of higher order. The absence of boundary fitted elements in fictitious domain or immersed boundary methods significantly restricts a strong enforcement of essential boundary conditions to models where the boundary of the solution domain coincides with the embedding analysis domain. Penalty methods and Lagrange multiplier methods are adequate means to overcome this limitation but often suffer from various drawbacks with severe consequences for a stable and accurate solution of the governing system of equations. In this contribution, we follow the idea of NITSCHE [29] who developed a stable scheme for the solution of the Laplace problem taking weak boundary conditions into account. An extension to problems from linear elasticity shows an appropriate behavior with regard to numerical stability, accuracy and an adequate convergence behavior. NURBS are chosen as a high-order approximation basis to benefit from their smoothness and flexibility in the process of uniform model refinement.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ruess, Dr Martin
• Authors: Ruess, M., Bazilevs, Y., Schillinger, D., Zander, N., and Rank, E.
• College/School: College of Science and Engineering > School of Engineering > Infrastructure and Environment
• ISBN: 9783950248197
• Copyright Holders: Copyright © 2012 The Authors
• Publisher Policy: Reproduced with the permission of the author.

Related URLs

• Organisation