Density-Sensitive Implicit Functions Using Sub-Voxel Sampling in Additive Manufacturing

Abstract

In the context of lattice-based design and manufacturing, the problem of physical realization of density maps into lattices of a particular family is central. Density maps are prescribed by design optimization algorithms, which seek to fulfill structural demands on a workpiece, while saving material. These density maps cannot be directly manufactured since local graded densities cannot be achieved using the bulk solid material. Because of this reason, existing topology optimization approaches bias the local voxel relative density to either 0 (void) or 1 (filled). Additive manufacturing opens possibilities to produce graded density individuals belonging to different lattice families. However, voxel-level sampled boundary representations of the individuals produce rough and possibly disconnected shells. In response to this limitation, this article uses sub-voxel sampling (largely unexploited in the literature) to generate lattices of graded densities. This sub-voxel sampling eliminates the risk of shell disconnections and renders better surface continuity. The manuscript devises a function to produce Schwarz cells that materialize a given relative density. This article illustrates a correlation of continuity against stress concentration by simulating C0 and C1 inter-lattice continuity. The implemented algorithm produces implicit functions and thus lattice designs which are suitable for metal additive manufacturing and able to achieve the target material savings. The resulting workpieces, produced by outsource manufacturers, are presented. Additional work is required in the modeling of the mechanical response (stress/strain/deformation) and response of large lattice sets (with arbitrary geometry and topology) under working loads.

BIB_text

@Article {
title = {Density-Sensitive Implicit Functions Using Sub-Voxel Sampling in Additive Manufacturing},
journal = {Metals},
pages = {1293},
volume = {9},
keywds = {
additive manufacturing; 3D printing; topology optimization; Schwarz Primitive; lattice structure; Industry 4.0
}
abstract = {

In the context of lattice-based design and manufacturing, the problem of physical realization of density maps into lattices of a particular family is central. Density maps are prescribed by design optimization algorithms, which seek to fulfill structural demands on a workpiece, while saving material. These density maps cannot be directly manufactured since local graded densities cannot be achieved using the bulk solid material. Because of this reason, existing topology optimization approaches bias the local voxel relative density to either 0 (void) or 1 (filled). Additive manufacturing opens possibilities to produce graded density individuals belonging to different lattice families. However, voxel-level sampled boundary representations of the individuals produce rough and possibly disconnected shells. In response to this limitation, this article uses sub-voxel sampling (largely unexploited in the literature) to generate lattices of graded densities. This sub-voxel sampling eliminates the risk of shell disconnections and renders better surface continuity. The manuscript devises a function to produce Schwarz cells that materialize a given relative density. This article illustrates a correlation of continuity against stress concentration by simulating C0 and C1 inter-lattice continuity. The implemented algorithm produces implicit functions and thus lattice designs which are suitable for metal additive manufacturing and able to achieve the target material savings. The resulting workpieces, produced by outsource manufacturers, are presented. Additional work is required in the modeling of the mechanical response (stress/strain/deformation) and response of large lattice sets (with arbitrary geometry and topology) under working loads.


}
doi = {10.3390/met9121293},
date = {2019-11-30},
}
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