AUTONOMOUS STRUCTURAL LAYOUT AND TOPOLOGY OPTIMIZATION
| dc.contributor.advisor | Kobayashi, Marcelo H. | |
| dc.contributor.author | Melnichenko, Igor Olegovich | |
| dc.contributor.department | Mechanical Engineering | |
| dc.date.accessioned | 2024-10-09T23:45:41Z | |
| dc.date.available | 2024-10-09T23:45:41Z | |
| dc.date.issued | 2024 | |
| dc.description.degree | M.S. | |
| dc.identifier.uri | https://hdl.handle.net/10125/108659 | |
| dc.subject | Mechanical engineering | |
| dc.subject | Autonomous | |
| dc.subject | Layout | |
| dc.subject | Optimization | |
| dc.subject | Topology | |
| dc.title | AUTONOMOUS STRUCTURAL LAYOUT AND TOPOLOGY OPTIMIZATION | |
| dc.type | Thesis | |
| dcterms.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. | |
| dcterms.extent | 60 pages | |
| dcterms.language | en | |
| dcterms.publisher | University of Hawai'i at Manoa | |
| dcterms.rights | All UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner. | |
| dcterms.type | Text | |
| local.identifier.alturi | http://dissertations.umi.com/hawii:12270 |
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