AUTONOMOUS STRUCTURAL LAYOUT AND TOPOLOGY OPTIMIZATION
Date
2024
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Abstract
This thesis utilizes a biology-inspired method for topology optimization in structures. Themethod is adapted from an existing method that utilizes cellular division to generate
topology maps for structures. These maps are generated from genomes that are created by
a genetic algorithm. Once the topologies are created, they go through sizing optimization
and are then evaluated based on their weight. The weight is returned to the genetic
algorithm as fitness to optimize the topologies further. This method adds two new features
to the optimization process. One of the features is to allow the genetic algorithm to control
whether any specific load-bearing substructure within the structure is an I-beam or a truss.
The other feature is to let the genetic algorithm also optimize the topology of the truss
sub-structure. Optimization runs were performed on a desktop computer with a small
population size and then at a supercomputing facility with a larger population. The results
of these runs were compared against a baseline design with a conventional topology.
Weight reductions of about 4% were achieved.
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Mechanical engineering, Autonomous, Layout, Optimization, Topology
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60 pages
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