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Aerodynamic Shape Design by Evolutionary Optimization and Support Vector Machines

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Application of Surrogate-based Global Optimization to Aerodynamic Design

Part of the book series: Springer Tracts in Mechanical Engineering ((STME))

Abstract

This paper proposes a computational methodology for the aerodynamic shape design of aeronautical configurations, aiming a broad and efficient exploration of the design space. A novel adaptive sampling technique focused on the global optimization problem, the Intelligent Estimation Search with Sequential Learning (IES-SL), is presented. This approach is based on the use of Support Vector Machines (SVMs) as the surrogate model for estimating the objective function, in combination with an evolutionary algorithm (EA) to enable the discovery of global optima. The proposed methodology is applied to improve the aerodynamic performance of a two-dimensional airfoil and a three-dimensional wing and results on surrogate model validation and optimization-focused sampling criteria are discussed.

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Acknowledgements

The research described in this paper made by INTA, UAH and UPM researchers has been supported under the INTA activity “Termofluidodinámica” (IGB99001). This work is also partially supported by Spanish Ministry of Science and Innovation, under a project number ECO2010-22065-C03-02.

The experiments performed in this paper are also part of a GARTEUR action group (www.garteur.org) that has been established to explore these SBGO approaches. The main objective of the action group is, by means of a European collaborative research, to make a deep evaluation and assessment of SBGO methods for aerodynamic shape design, dealing with the main challenges as the curse of dimensionality, reduction of the design space and error metrics for validation, amongst others.

Author information

Authors and Affiliations

  1. Fluid Dynamics Branch, Spanish National Institute for Aerospace Technology (ISDEFE/INTA), Ctra. Ajalvir, km. 4, 28850, Torrejón de Ardoz, Spain

    Esther Andrés-Pérez

  2. Department of Signal Theory and Communications, Universidad de Alcalá (UAH), Ctra. Madrid-Barcelona km. 33, 28802, Alcalá de Henares, Spain

    Leopoldo Carro-Calvo & Sancho Salcedo-Sanz

  3. School of Aeronautics, Universidad Politécnica de Madrid (UPM), Plaza del Cardenal Cisneros 3, 28040, Madrid, Spain

    Mario J. Martin-Burgos

Authors
  1. Esther Andrés-Pérez
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  2. Leopoldo Carro-Calvo
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  3. Sancho Salcedo-Sanz
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  4. Mario J. Martin-Burgos
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Corresponding author

Correspondence to Esther Andrés-Pérez .

Editor information

Editors and Affiliations

  1. CIRA, the Italian Aerospace Research Center, Capua (CE), Italy

    Emiliano Iuliano

  2. INTA, Spanish National Institute for Aerospace Technology, Torrejón de Ardoz, Spain

    Esther Andrés Pérez

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Andrés-Pérez, E., Carro-Calvo, L., Salcedo-Sanz, S., Martin-Burgos, M.J. (2016). Aerodynamic Shape Design by Evolutionary Optimization and Support Vector Machines. In: Iuliano, E., Pérez, E. (eds) Application of Surrogate-based Global Optimization to Aerodynamic Design. Springer Tracts in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-21506-8_1

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  • DOI: https://doi.org/10.1007/978-3-319-21506-8_1

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21505-1

  • Online ISBN: 978-3-319-21506-8

  • eBook Packages: EngineeringEngineering (R0)

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