Reduced-order, trajectory piecewise-linear models for nonlinear computational fluid dynamics
A trajectory piecewise-linear (TPWL) approach is developed for a computational fluid dynamics (CFD) model of the two-dimensional Euler equations. The approach uses a weighted combination of linearized models to represent the nonlinear CFD system. The proper orthogonal decomposition (POD) is then use...
| Main Authors: | , |
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| Format: | Article |
| Language: | en_US |
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2003
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/3892 |
| _version_ | 1826194094949400576 |
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| author | Gratton, David Willcox, Karen E. |
| author_facet | Gratton, David Willcox, Karen E. |
| author_sort | Gratton, David |
| collection | MIT |
| description | A trajectory piecewise-linear (TPWL) approach is developed for a computational fluid dynamics (CFD) model of the two-dimensional Euler equations. The approach uses a weighted combination of linearized models to represent the nonlinear CFD system. The proper orthogonal decomposition (POD) is then used to create a reduced-space basis, onto which the TPWL model is projected. This projection yields an efficient reduced-order model of the nonlinear system, which does not require the evaluation of any full-order system residuals. The method is applied to the case of flow through an actively controlled supersonic diffuser. With an appropriate choice of linearization points and POD basis vectors, the method is found to yield accurate results, including cases with significant shock motion. |
| first_indexed | 2024-09-23T09:50:24Z |
| format | Article |
| id | mit-1721.1/3892 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:50:24Z |
| publishDate | 2003 |
| record_format | dspace |
| spelling | mit-1721.1/38922019-04-18T03:00:31Z Reduced-order, trajectory piecewise-linear models for nonlinear computational fluid dynamics Gratton, David Willcox, Karen E. trajectory piecewise-linear models non-linear computational fluid dynamics proper orthogonal decomposition A trajectory piecewise-linear (TPWL) approach is developed for a computational fluid dynamics (CFD) model of the two-dimensional Euler equations. The approach uses a weighted combination of linearized models to represent the nonlinear CFD system. The proper orthogonal decomposition (POD) is then used to create a reduced-space basis, onto which the TPWL model is projected. This projection yields an efficient reduced-order model of the nonlinear system, which does not require the evaluation of any full-order system residuals. The method is applied to the case of flow through an actively controlled supersonic diffuser. With an appropriate choice of linearization points and POD basis vectors, the method is found to yield accurate results, including cases with significant shock motion. Singapore-MIT Alliance (SMA) 2003-12-14T23:07:43Z 2003-12-14T23:07:43Z 2004-01 Article http://hdl.handle.net/1721.1/3892 en_US High Performance Computation for Engineered Systems (HPCES); 287560 bytes application/pdf application/pdf |
| spellingShingle | trajectory piecewise-linear models non-linear computational fluid dynamics proper orthogonal decomposition Gratton, David Willcox, Karen E. Reduced-order, trajectory piecewise-linear models for nonlinear computational fluid dynamics |
| title | Reduced-order, trajectory piecewise-linear models for nonlinear computational fluid dynamics |
| title_full | Reduced-order, trajectory piecewise-linear models for nonlinear computational fluid dynamics |
| title_fullStr | Reduced-order, trajectory piecewise-linear models for nonlinear computational fluid dynamics |
| title_full_unstemmed | Reduced-order, trajectory piecewise-linear models for nonlinear computational fluid dynamics |
| title_short | Reduced-order, trajectory piecewise-linear models for nonlinear computational fluid dynamics |
| title_sort | reduced order trajectory piecewise linear models for nonlinear computational fluid dynamics |
| topic | trajectory piecewise-linear models non-linear computational fluid dynamics proper orthogonal decomposition |
| url | http://hdl.handle.net/1721.1/3892 |
| work_keys_str_mv | AT grattondavid reducedordertrajectorypiecewiselinearmodelsfornonlinearcomputationalfluiddynamics AT willcoxkarene reducedordertrajectorypiecewiselinearmodelsfornonlinearcomputationalfluiddynamics |