Spectral Coefficient Analysis on Geometerical Deformation using Laplace-Beltrami Operator
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Publisher:The Ohio State University
Series/Report no.:The Ohio State University. Department of Mechanical and Aerospace Engineering Undergraduate Research Theses; 2020
Automotive part design consists of crash simulation and design optimization done by finite-element computing software. In order to make these processes possible, the part geometry must be efficiently represented. Different parameters can be defined in an optimization in order to determine appropriate material models and part thickness, however there are still computational limitations on optimizing based on specific part deformation. This paper proposes a method that goes beyond tracking individual node displacements in order to use deformation as a parameter for optimized part design. Using a dimension reduction method, deformations of the part can be classified using a spectral descriptor corresponding to that deformation. This spectral descriptor is taken a step further and is used to efficiently filter a simulation bundle based on the defined desired geometric deformation. In addition, this spectral descriptor is used for part reconstruction with a higher visual accuracy compared to traditional reconstruction methods. Finally, this paper proposes application of this method into design optimization using a machine learning approach.
Academic Major: Mechanical Engineering