Flow Field Data Mining of Pareto-Optimal Airfoils Using Proper Orthogonal Decomposition

Akira Oyama; Paul C. Verburg; Taku Nonomura; Harry W.M. Hoeijmakers; Kozo Fuji

doi:10.2514/6.2010-1140

Flow Field Data Mining of Pareto-Optimal Airfoils Using Proper Orthogonal Decomposition

Akira Oyama
, Paul C. Verburg
, Taku Nonomura
, Harry W.M. Hoeijmakers
, Kozo Fuji

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

14 Citations (Scopus)

Abstract

The capability of a proper-orthogonal-decomposition-based data mining approach for the analysis of flow field data of Pareto-optimal solutions is demonstrated. This method enables a designer to extract design knowledge by examining baseline data and a limited number of eigenvectors and orthogonal base vectors. The flow data analyzed herein are the pressure field data of the Pareto-optimal solutions of an aerodynamic transonic airfoil shape optimization problem. The results of the present study indicate that the proper-orthogonal- decomposition-based data mining approach is useful for extracting design knowledge from the flow field data of the Pareto-optimal solutions.

Original language	English
Title of host publication	Proceedings 48th AIAA Aerospace Sciences Meeting 2010
Subtitle of host publication	Including the New Horizons Forum and Aerospace Exposition
Editors	George K. Muellner
Place of Publication	Orlando, FL, USA
Publisher	American Institute of Aeronautics and Astronautics
Pages	1-11
ISBN (Electronic)	978-1-60086-959-4
DOIs	https://doi.org/10.2514/6.2010-1140
Publication status	Published - 4 Jan 2010
Event	48th AIAA Aerospace Sciences Meeting 2010: including The New Horizons Forum and Aerospace Exposition - Orlando, United States Duration: 4 Jan 2010 → 7 Jan 2010 Conference number: 48

Conference

Conference	48th AIAA Aerospace Sciences Meeting 2010
Country/Territory	United States
City	Orlando
Period	4/01/10 → 7/01/10

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10.2514/6.2010-1140

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Oyama, A., Verburg, P. C., Nonomura, T., Hoeijmakers, H. W. M., & Fuji, K. (2010). Flow Field Data Mining of Pareto-Optimal Airfoils Using Proper Orthogonal Decomposition. In G. K. Muellner (Ed.), Proceedings 48th AIAA Aerospace Sciences Meeting 2010: Including the New Horizons Forum and Aerospace Exposition (pp. 1-11). American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2010-1140

Oyama, Akira ; Verburg, Paul C. ; Nonomura, Taku et al. / Flow Field Data Mining of Pareto-Optimal Airfoils Using Proper Orthogonal Decomposition. Proceedings 48th AIAA Aerospace Sciences Meeting 2010: Including the New Horizons Forum and Aerospace Exposition. editor / George K. Muellner. Orlando, FL, USA : American Institute of Aeronautics and Astronautics, 2010. pp. 1-11

@inproceedings{2141ede078cb44b0a8c4564acac5b927,

title = "Flow Field Data Mining of Pareto-Optimal Airfoils Using Proper Orthogonal Decomposition",

abstract = "The capability of a proper-orthogonal-decomposition-based data mining approach for the analysis of flow field data of Pareto-optimal solutions is demonstrated. This method enables a designer to extract design knowledge by examining baseline data and a limited number of eigenvectors and orthogonal base vectors. The flow data analyzed herein are the pressure field data of the Pareto-optimal solutions of an aerodynamic transonic airfoil shape optimization problem. The results of the present study indicate that the proper-orthogonal- decomposition-based data mining approach is useful for extracting design knowledge from the flow field data of the Pareto-optimal solutions.",

author = "Akira Oyama and Verburg, \{Paul C.\} and Taku Nonomura and Hoeijmakers, \{Harry W.M.\} and Kozo Fuji",

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booktitle = "Proceedings 48th AIAA Aerospace Sciences Meeting 2010",

publisher = "American Institute of Aeronautics and Astronautics",

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note = "48th AIAA Aerospace Sciences Meeting 2010 : including The New Horizons Forum and Aerospace Exposition ; Conference date: 04-01-2010 Through 07-01-2010",

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Oyama, A, Verburg, PC, Nonomura, T, Hoeijmakers, HWM & Fuji, K 2010, Flow Field Data Mining of Pareto-Optimal Airfoils Using Proper Orthogonal Decomposition. in GK Muellner (ed.), Proceedings 48th AIAA Aerospace Sciences Meeting 2010: Including the New Horizons Forum and Aerospace Exposition. American Institute of Aeronautics and Astronautics, Orlando, FL, USA, pp. 1-11, 48th AIAA Aerospace Sciences Meeting 2010, Orlando, Florida, United States, 4/01/10. https://doi.org/10.2514/6.2010-1140

Flow Field Data Mining of Pareto-Optimal Airfoils Using Proper Orthogonal Decomposition. / Oyama, Akira; Verburg, Paul C.; Nonomura, Taku et al.
Proceedings 48th AIAA Aerospace Sciences Meeting 2010: Including the New Horizons Forum and Aerospace Exposition. ed. / George K. Muellner. Orlando, FL, USA: American Institute of Aeronautics and Astronautics, 2010. p. 1-11.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Flow Field Data Mining of Pareto-Optimal Airfoils Using Proper Orthogonal Decomposition

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AU - Hoeijmakers, Harry W.M.

AU - Fuji, Kozo

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N2 - The capability of a proper-orthogonal-decomposition-based data mining approach for the analysis of flow field data of Pareto-optimal solutions is demonstrated. This method enables a designer to extract design knowledge by examining baseline data and a limited number of eigenvectors and orthogonal base vectors. The flow data analyzed herein are the pressure field data of the Pareto-optimal solutions of an aerodynamic transonic airfoil shape optimization problem. The results of the present study indicate that the proper-orthogonal- decomposition-based data mining approach is useful for extracting design knowledge from the flow field data of the Pareto-optimal solutions.

AB - The capability of a proper-orthogonal-decomposition-based data mining approach for the analysis of flow field data of Pareto-optimal solutions is demonstrated. This method enables a designer to extract design knowledge by examining baseline data and a limited number of eigenvectors and orthogonal base vectors. The flow data analyzed herein are the pressure field data of the Pareto-optimal solutions of an aerodynamic transonic airfoil shape optimization problem. The results of the present study indicate that the proper-orthogonal- decomposition-based data mining approach is useful for extracting design knowledge from the flow field data of the Pareto-optimal solutions.

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DO - 10.2514/6.2010-1140

M3 - Conference contribution

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BT - Proceedings 48th AIAA Aerospace Sciences Meeting 2010

A2 - Muellner, George K.

PB - American Institute of Aeronautics and Astronautics

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T2 - 48th AIAA Aerospace Sciences Meeting 2010

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Oyama A, Verburg PC, Nonomura T, Hoeijmakers HWM, Fuji K. Flow Field Data Mining of Pareto-Optimal Airfoils Using Proper Orthogonal Decomposition. In Muellner GK, editor, Proceedings 48th AIAA Aerospace Sciences Meeting 2010: Including the New Horizons Forum and Aerospace Exposition. Orlando, FL, USA: American Institute of Aeronautics and Astronautics. 2010. p. 1-11 doi: 10.2514/6.2010-1140

Flow Field Data Mining of Pareto-Optimal Airfoils Using Proper Orthogonal Decomposition

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