Model Reduction for Large-Scale Systems with High Dimensional Parametric Input Space

Model Reduction for Large-Scale Systems with High Dimensional Parametric Input Space

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A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a reduced basis approach, which requires the computation of high-fidelity solutions at a number of sample points throughou...

תיאור מלא

מידע ביבליוגרפי
Main Authors: Bui-Thanh, T., Willcox, K., Ghattas, O.
פורמט: Technical Report
שפה:en_US
יצא לאור: Aerospace Computational Design Laboratory, Dept. of Aeronautics & Astronautics, Massachusetts Institute of Technology 2010
נושאים:
model reduction
optimization
sampling
heat conduction
גישה מקוונת:http://hdl.handle.net/1721.1/57591

אינטרנט

http://hdl.handle.net/1721.1/57591

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