CAD Defeaturing using Machine Learning
Abstract not provided.
Publications
SNL Data and Visualization: ML Projects at Sandia
Abstract not provided.
Machine Learning-based CAD Defeaturing for Tetrahedral Mesh Generation
Abstract not provided.
Defeaturing using Machine Learning
Abstract not provided.
Automated Simulation Model Preparation with Machine Learning
Abstract not provided.
Topology Optimization of Cellular Structure
This paper presents an end-to-end design process for compliance minimization based topological optimization of cellular structures through to the realization of a final printed product. Homogenization is used to derive properties representative of these structures through direct numerical simulation of unit cell models of the underlying periodic structure. The resulting homogenized properties are then used assuming uniform distribution of the cellular structure to compute the final macro-scale structure. A new method is then presented for generating an STL representation of the final optimized part that is suitable for printing on typical industrial machines. Quite fine cellular structures are shown to be possible using this method as compared to other approaches that use nurb based CAD representations of the geometry. Finally, results are presented that illustrate the fine-scale stresses developed in the final macro-scale optimized part and suggestions are made as to incorporate these features into the overall optimization process.
PLATO Platinum Topology Optimization
Abstract not provided.
Applying template-based generic programming to the simulation and analysis of partial differential equations
Scientific Programming
Abstract not provided.
A Comparison of 3D Mesh Morphing Methods for CAD Based Shape Optimization
Abstract not provided.
A Comparison of Mesh Morphing Methods for 3D Shape Optimization
Abstract not provided.
Building a PDE with Componenets including shape optimization and embedded UQ
Abstract not provided.
pCAMAL: An embarrassingly parallel hexahedral mesh generator
Proceedings of the 16th International Meshing Roundtable, IMR 2007
This paper describes a distributed-memory, embarrassingly parallel hexahedral mesh generator, pCAMAL (parallel CUBIT Adaptive Mesh Algorithm Library). pCAMAL utilizes the sweeping method following a serial step of geometry decomposition conducted in the CUBIT geometry preparation and mesh generation tool. The utility of pCAMAL in generating large meshes is illustrated, and linear speed-up under load-balanced conditions is demonstrated.
Immersive Topology Environment for Meshing
Abstract not provided.
A Framework for Sizing Function Generation in Assembly Meshing
Abstract not provided.
An Immersive Topology Environment for Meshing
Abstract not provided.
15 Results