Search Results for author:
Found 5 papers, 0 papers with code
PATO: Producibility-Aware Topology Optimization using Deep Learning for Metal Additive Manufacturing
In this paper, we propose PATO-a producibility-aware topology optimization (TO) framework to help efficiently explore the design space of components fabricated using metal additive manufacturing (AM), while ensuring manufacturability with respect to cracking.
Curvy: An Interactive Design Tool for Varying Density Support Structures
Combined with the build orientation optimization, Curvy provides a practical solution to the design of support structures with minimal perceptual or functional impact on the target part to be printed.
Graphics Computational Geometry
Structural Design Using Laplacian Shells
We introduce a method to design lightweight shell objects that are structurally robust under the external forces they may experience during use.
Enhancing the Structural Performance of Additively Manufactured Objects
The ability to accurately quantify the performance an additively manufactured (AM) product is important for a widespread industry adoption of AM as the design is required to: (1) satisfy geometrical constraints, (2) satisfy structural constraints dictated by its intended function, and (3) be cost effective compared to traditional manufacturing methods.
Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty
Our approach uses a computationally tractable experimental design method to select number of sample force locations based on geometry only, without inspecting the stress response that requires computationally expensive finite-element analysis.
