Dimensionality reduction for shape optimization

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

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The method provides opportunities for assessing, comparing, and reducing in dimensionality different design spaces, defining efficiently the geometric parametrization for complex shape optimization problems.

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