Aerodynamic Shape Design by Evolutionary Optimization and Support Vector Machines

  • Esther Andrés-PérezEmail author
  • Leopoldo Carro-Calvo
  • Sancho Salcedo-Sanz
  • Mario J. Martin-Burgos
Part of the Springer Tracts in Mechanical Engineering book series (STME)


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.


Aerodynamic shape optimization Evolutionary algorithms Support vector machines Surrogate-based global optimization 



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 ( 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.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Esther Andrés-Pérez
    • 1
    Email author
  • Leopoldo Carro-Calvo
    • 2
  • Sancho Salcedo-Sanz
    • 2
  • Mario J. Martin-Burgos
    • 3
  1. 1.Fluid Dynamics Branch, Spanish National Institute for Aerospace Technology (ISDEFE/INTA)Torrejón de ArdozSpain
  2. 2.Department of Signal Theory and CommunicationsUniversidad de Alcalá (UAH)Alcalá de HenaresSpain
  3. 3.School of AeronauticsUniversidad Politécnica de Madrid (UPM)MadridSpain

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