Reduced-Order modeling of complex systems with multiple system parameters

  • Authors:
  • Max Gunzburger;Janet Peterson

  • Affiliations:
  • School of Computational Sciences, Florida State University, Tallahassee, FL;School of Computational Sciences, Florida State University, Tallahassee, FL

  • Venue:
  • LSSC'05 Proceedings of the 5th international conference on Large-Scale Scientific Computing
  • Year:
  • 2005

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Abstract

The computational approximation of solutions of complex systems such as the Navier-Stokes equations is often a formidable task. For example, in feedback control settings where one often needs solutions of the complex systems in real time, it would be impossible to use large-scale finite element or finite-volume or spectral codes. For this reason, there has been much interest in the development of low-dimensional models that can accurately be used to simulate and control complex systems. Reduced-order modeling approaches based on proper orthogonal decompositions and centroidal Voronoi tessellations are discussed. The important implementation issue of how boundary conditions containing multiple parameters are handled in the reduced-order modeling context is highlighted.