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.
Supported in part by Sandia National Laboratories under contracts 233519 and 406670.
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Gunzburger, M., Peterson, J. (2006). Reduced-Order Modeling of Complex Systems with Multiple System Parameters. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2005. Lecture Notes in Computer Science, vol 3743. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11666806_2
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DOI: https://doi.org/10.1007/11666806_2
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