Data-driven stochastic optimization on manifolds for additive manufacturing

Computational Materials Science（2020）

引用 14|浏览4

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摘要

•We infer the dependency structure between build parameters and tensile properties.•The method performs manifold kernel density estimation in a diffusion-maps embedding.•We reveal the efficient frontier and enable optimization of arbitrary objectives.

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关键词

Additive manufacturing,Diffusion maps,Kernel density estimation,Stochastic optimization,Laser powder-bed fusion

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