期刊
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS
卷 63, 期 2, 页码 207-230出版社
WILEY
DOI: 10.1002/fld.2089
关键词
interpolation; parameterized reduced-order models; spline; Riemannian manifold; Kriging; design
Model reduction has significant potential in design, optimization and probabilistic analysis applications, but including the parameter dependence in the reduced-order model (ROM) remains challenging. In this work, interpolation among reduced-order matrices is proposed as a means to obtain parameterized ROMs. These ROMs are fast to evaluate and solve, and can be constructed without reference to the original full-order model. Spline interpolation of the reduced-order system matrices in the original space and in the space tangent to the Riemannian manifold is compared with Kriging interpolation of the predicted outputs. A heuristic criterion to select the most appropriate interpolation space is proposed. The interpolation approach is applied to a steady-state thermal design problem and probabilistic analysis via Monte Carlo simulation of an unsteady contaminant transport problem. Copyright (C) 2009 John Wiley & Sons, Ltd.
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