Projection‐based model reduction for contact problems

Abstract

To be feasible for computationally intensive applications such as parametric studies, optimization, and control design, large‐scale finite element analysis requires model order reduction. This is particularly true in nonlinear settings that tend to dramatically increase computational complexity. Although significant progress has been achieved in the development of computational approaches for the reduction of nonlinear computational mechanics models, addressing the issue of contact remains a major hurdle. To this effect, this paper introduces a projection‐based model reduction approach for both static and dynamic contact problems. It features the application of a non‐negative matrix factorization scheme to the construction of a positive reduced‐order basis for the contact forces, and a greedy sampling algorithm coupled with an error indicator for achieving robustness with respect to model parameter variations. The proposed approach is successfully demonstrated for the reduction of several two‐dimensional, simple, but representative contact and self contact computational models. Copyright © 2015 John Wiley & Sons, Ltd.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 12, 2015
Source ID
10.1002/nme.5135

Entities

People

  • Charbel Farhat
  • David Amsallem
  • Maciej Balajewicz

Organizations

  • Office of Naval Research
  • Stanford University
  • University of Illinois Urbana–Champaign

Tags

Readers

  • Graph Algorithms and Convex Optimization.
  • Neural Network Machine Learning.
  • Systems Analysis and Design