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Reduced order techniques for sensiti...

Parrish, Jefferson Carter.

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Reduced order techniques for sensitivity analysis and design optimization of aerospace systems.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Reduced order techniques for sensitivity analysis and design optimization of aerospace systems./
作者:	Parrish, Jefferson Carter.
面頁冊數:	199 p.
附註:	Source: Dissertation Abstracts International, Volume: 75-08(E), Section: B.
Contained By:	Dissertation Abstracts International75-08B(E).
標題:	Engineering, Aerospace. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3618312
ISBN:	9781303865268

Reduced order techniques for sensitivity analysis and design optimization of aerospace systems.
Parrish, Jefferson Carter.

Reduced order techniques for sensitivity analysis and design optimization of aerospace systems. - 199 p.

Source: Dissertation Abstracts International, Volume: 75-08(E), Section: B.

Thesis (Ph.D.)--Mississippi State University, 2014.

This work proposes a new method for using reduced order models in lieu of high fidelity analysis during the sensitivity analysis step of gradient based design optimization. The method offers a reduction in the computational cost of finite difference based sensitivity analysis in that context.

ISBN: 9781303865268Subjects--Topical Terms:

1018395
Engineering, Aerospace.

Reduced order techniques for sensitivity analysis and design optimization of aerospace systems.
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020 $a 9781303865268
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100 1 $a Parrish, Jefferson Carter. $3 2103079
245 1 0 $a Reduced order techniques for sensitivity analysis and design optimization of aerospace systems.
300 $a 199 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-08(E), Section: B.
500 $a Advisers: Masoud Rais-Rohani; J. Mark Janus.
502 $a Thesis (Ph.D.)--Mississippi State University, 2014.
520 $a This work proposes a new method for using reduced order models in lieu of high fidelity analysis during the sensitivity analysis step of gradient based design optimization. The method offers a reduction in the computational cost of finite difference based sensitivity analysis in that context.
520 $a The method relies on interpolating reduced order models which are based on proper orthogonal decomposition. The interpolation process is performed using radial basis functions and Grassmann manifold projection. It does not require additional high fidelity analyses to interpolate a reduced order model for new points in the design space. The interpolated models are used specifically for points in the finite difference stencil during sensitivity analysis.
520 $a The proposed method is applied to an airfoil shape optimization (ASO) problem and a transport wing optimization (TWO) problem. The errors associated with the reduced order models themselves as well as the gradients calculated from them are evaluated. The effects of the method on the overall optimization path, computation times, and function counts are also examined.
520 $a The ASO results indicate that the proposed scheme is a viable method for reducing the computational cost of these optimizations. They also indicate that the adaptive step is an effective method of improving interpolated gradient accuracy. The TWO results indicate that the interpolation accuracy can have a strong impact on optimization search direction.
590 $a School code: 0132.
650 4 $a Engineering, Aerospace. $3 1018395
650 4 $a Applied Mathematics. $3 1669109
650 4 $a Computer Science. $3 626642
690 $a 0538
690 $a 0364
690 $a 0984
710 2 $a Mississippi State University. $b Computational Engineering. $3 1680835
773 0 $t Dissertation Abstracts International $g 75-08B(E).
790 $a 0132
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3618312