What is it about?
The paper is about reducing the dimensionality of design spaces in shape optimization. The technique works offline, is based on the geometric variability, and does not require any objective function evaluation.
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Why is it important?
This is an offline method that does not require any objective function evaluation. The design space assessment and dimensionality reduction takes place before optimization is performed.
Perspectives
The method provides opportunities for assessing, comparing, and reducing in dimensionality different design spaces, defining efficiently the geometric parametrization for complex shape optimization problems.
Dr Matteo Diez
CNR-INSEAN, National Research Council-Marine Technology Research Institute, Rome, Italy
Read the Original
This page is a summary of: Design Space Dimensionality Reduction for Single- and Multi-Disciplinary Shape Optimization, June 2016, American Institute of Aeronautics and Astronautics (AIAA),
DOI: 10.2514/6.2016-4295.
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