A deterministic approach for shape and topology optimisation under material uncertainty in additive manufacturing

Abstract

The present work aims at handling uncertain materials in shape and topology optimisation applied to additive manufacturing. More specifically, we minimise an objective function combining the mean values of standard cost functions and assume that the uncertainties are small and generated by two random variables. These two variables representing the amplitude of the Young's modulus correspond to the zone of porosity inclusion and surface roughness defects. A deterministic approach that relies on a secondorder Taylor expansion of the cost function has been proposed by Allaire & Dapogny [2]. The present work proposes a general framework to handle uncertainties of the Young's modulus in which its amplitude is divided into N zones and then applied onto two zones corresponding to the porosity inclusion and surface roughness defects. We demonstrate the effectiveness of the approach in the context of the level-set-based topology optimisation for the robust compliance minimisation of three-dimensional cantilever test cases.

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