In this work, we propose a methodology to model and simulate spatially-varying material parameters on geometries obtained through additive manufacturing. The construction of the probabilistic representation is first presented, and aspects related to physical consistency and well-posedness are discussed. We then discuss sampling issues on complex, highly-porous domains. A methodology for addressing inverse identification is finally discussed and illustrated.

Stochastic Modeling and Generation of Material Properties on Geometries Produced by Additive Manufacturing

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