| dc.identifier.uri | http://hdl.handle.net/11401/78894 | |
| dcterms.abstract | The design of structure is a research topic explored by human beings for hundreds of
years. However, for a long period of time, the designing process is always an experience or
inspiration based tinkering rather than a scientifically based technology. As the designing
requirements become complicated, the intuition based designs may not work effectively
as expected. Topology optimization, on the other hand, has the potential to systematically
generate designs at their optimal performance without requiring a priori knowledge. This
powerful tool has been utilized for decades and has seen a wide application in many
engineering fields. Here in this thesis, the shape and topology optimization of designs
are carried out within the framework of the level set approach. During the optimization,
the design is implicitly represented by the zero level of a one-dimension-higher hypersurface
which is referred as the level set function. By coupling the level set model with the
physical model, the design performance can be evaluated in each optimization iteration
to provide feedback to the designing process. With the feedback information, the level
set function is updated accordingly until the final optimal structural layout is achieved.
With the help of the level set methods, the topological change of the design, including
splitting and merging can be handled in a natural way. | |
| dcterms.available | 2019-01-01 | |
| dcterms.contributor | Advisor: Chen, Shikui | |
| dcterms.contributor | Committee members: Ge, Jeffrey; Nakamura, Toshio; Jiao, Xiangmin | |
| dcterms.creator | Jiang, Long | |
| dcterms.date | 2019 | |
| dcterms.dateAccepted | 2019-12-06T17:23:45Z | |
| dcterms.dateSubmitted | 2019-12-06T17:23:45Z | |
| dcterms.description | Dissertation | |
| dcterms.description | Department of Mechanical Engineering | |
| dcterms.extent | 164 pages | |
| dcterms.format | application/pdf | |
| dcterms.issued | 2019-01-01 | |
| dcterms.language | en | |
| dcterms.provenance | Submitted by Jason Torre (fjason.torre@stonybrook.edu) on 2019-12-06T17:23:45Z
No. of bitstreams: 1
Jiang_grad.sunysb_0771E_14301.pdf: 56548926 bytes, checksum: bca5c327ebd9fad3c344d11ceb68087e (MD5) | |
| dcterms.provenance | Made available in DSpace on 2019-12-06T17:23:45Z (GMT). No. of bitstreams: 1
Jiang_grad.sunysb_0771E_14301.pdf: 56548926 bytes, checksum: bca5c327ebd9fad3c344d11ceb68087e (MD5)
Previous issue date: 2019 | |
| dcterms.publisher | Stony Brook University | |
| dcterms.title | Multiscale Structural Shape and Topology Optimization via a Variational Parametric Level Set Framework | |
| dcterms.type | Text | |
