Model Reduction for Large-Scale Systems with High Dimensional Parametric Input Space
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...
| Main Authors: | , , |
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| Format: | Technical Report |
| Language: | en_US |
| Published: |
Aerospace Computational Design Laboratory, Dept. of Aeronautics & Astronautics, Massachusetts Institute of Technology
2010
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/57591 |
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