Additive Manufacturability Analysis of Multiscale Aperiodic Structures: a Statistical Mechanics Approach

Abstract

Abstract Discrete, rule-based approaches to design for additive manufacturing can be inadequate or prohibitively complex for predicting the geometric fidelity of multiscale aperiodic structures that lack a representative volume element. In this paper, we introduce heuristics based upon statistical mechanics to assist in additive manufacturability analysis. The heuristics are derived from the following topological properties of complex network representations of the geometry of multiscale aperiodic structures: giant component size, node degree, average shortest path length, and robustness. We apply these heuristics to the design and additive manufacture of crumpled thin sheets, selected for their multiscale aperiodicity and reproducible statistical properties. Manufacturability is assessed by comparing these topo-logical network properties between a computationally designed crumpled structure and a microCT scan of an additively manufactured crumpled structure. Dimensionality reduction is performed on each network representation to balance spatial noise reduction and information loss. Consistent with expectations, the heuristics and topological properties show that crumpled structures at higher compaction levels are more readily manufactured. The results show the significance of statistical mechanics in providing insight into the additive manufacturability of multiscale aperiodic structures. We conclude by discussing the generality of this approach for alternative geometries and provide designers with a framework for interpreting manufacturability from a statistical mechanics perspective.