We introduce structural feasibility into procedural modeling of buildings. This allows for more realistic structural models that can be interacted with in physical simulations. While existing structural analysis tools focus heavily on providing an analysis of the stress state, our proposed method automatically tunes a set of designated free parameters to obtain forms that are structurally sound.

This paper introduces a perceptual model for determining 3D printing orientations. Additive manufacturing methods involving low-cost 3D printers often require robust branching support structures to prevent material collapse at overhangs. Although the designed shape can successfully be made by adding supports, residual material remains at the contact points after the supports have been removed, resulting in unsightly surface artifacts. Moreover, fine surface details on the fabricated model can easily be damaged while removing supports. To prevent the visual impact of these artifacts, we present a method to find printing directions that avoid placing supports in perceptually significant regions. Our model for preference in 3D printing direction is formulated as a combination of metrics including area of support, visual saliency, preferred viewpoint and smoothness preservation. We develop a training-and-learning methodology to obtain a closed-form solution for our perceptual model and perform a large-scale study. We demonstrate the performance of this perceptual model on both natural and man-made objects.

Figure 1: We propose a construction method for self-supporting structures that uses chains, instead of a dense formwork, to support the blocks during the intermediate construction stages. Our algorithm finds a work-minimizing sequence that guides the construction of the structure, indicating which chains are necessary to guarantee stability at each step. From left to right: a self-supporting structure, an intermediate construction stage with dense formwork, an intermediate construction stage with our method and the assembled model.