Procedural noises for the design of small-scale structures in Additive Manufacturing

Abstract

The democratization of AM has sparked a renewed interest in its potential applications. Among these, the ability to print small-scale structures is particularly promising: The geometry of internal small-scales structures directly influences the physical properties of the final parts. Thus, finding novel small-scales structures producing specific target properties expands the possibilities offered to additive manufacturing users, unlocking new potential applications in soft-robotics, for the design of prosthetics and orthoses, and for mechanical engineering at large. However, to be helpful in the wild, these small-scale structures have to expose controls over the properties they trigger -- and allow their variation in space -- so as to adapt their behavior to the user's intent. Interestingly, this type of spatial control over properties has been extensively studied in Computer Graphics, in particular for texture synthesis.

The objective of this thesis is to enable the same type of spatial control that is achieved by texture synthesis methods, for the synthesis of small-scale structures in Additive Manufacturing. In particular, I focused on defining strongly oriented small-scale structures. These trigger extremely anisotropic properties within the parts, a type of behavior that has not been extensively covered in prior works.

To achieve this, I proposed to revisit the \textit{procedural} formulations developed for texture synthesis in Computer Graphics, where each subpart of a pattern can be computed independently, only following local information. I successfully applied this approach to the generation of complex, oriented small-scale structures in large volumes. My first contribution is a novel approach for efficiently synthesizing highly contrasted oscillating patterns, that allows to closely follow property fields such as orientation and density while still being computed locally. I demonstrated this approach for texturing applications as well as for the synthesis of strongly oriented, anisotropic multi-material small-scale structures. This first method generates patterns that exhibit local defects, and therefore my second contribution extended this work to formulate a low-cost, efficient regularization technique that rectifies the oscillations. This led to the synthesis of freely orientable, self-supporting structures that can be used to trigger programmed deformations in 3D printed objects. My third contribution explores how to use a similar approach to define trajectories in fully filled 3D printed parts, under orientation objectives. By adjusting the phase of the oscillations, we are able to break the spatial alignments along the build direction that would otherwise result in local weaknesses in the produced parts.