Clustering approaches for faster nonlinear projection-based model order reduction
Abstract/Contents
- Abstract
- Projection-based model order reduction is a technology for dramatically reducing the cost of expensive computational physics simulations by approximately solving the governing equations in a data-driven approximation subspace. This dissertation proposes a set of techniques that exploit the concepts of locality and clustering to further accelerate reduced-order models on challenging problems. The first exploits the fact that many physical systems exhibit spatially localized features such as shocks or wakes to construct space-local reduced-order models that are more efficient than existing model-reduction schemes. The second takes advantage of locality in the simulation's state-space to construct smaller bases composed of a few nearby solution snapshots. Both novel techniques proposed here are applied to multiple systems drawn from computational fluid dynamics, including a challenging large-scale turbulent flow problem. In all applications, multiple orders of magnitude of speedup are observed relative to the original high-dimensional computational model, and substantial speedups are also observed relative to previously-existing model-order reduction techniques.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Anderson, Spenser Lamont |
|---|---|
| Degree supervisor | Farhat, Charbel |
| Thesis advisor | Farhat, Charbel |
| Thesis advisor | Alonso, Juan José, 1968- |
| Thesis advisor | Kochenderfer, Mykel J, 1980- |
| Degree committee member | Alonso, Juan José, 1968- |
| Degree committee member | Kochenderfer, Mykel J, 1980- |
| Associated with | Stanford University, Department of Aeronautics and Astronautics |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Spenser Anderson. |
|---|---|
| Note | Submitted to the Department of Aeronautics and Astronautics. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/nr627zx0684 |
Access conditions
- Copyright
- © 2023 by Spenser Lamont Anderson
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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