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Assessment of Inverse and Direct Methods for Airfoil and Wing Design

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Simulation-Driven Modeling and Optimization

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 153))

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Abstract

The goal of aerodynamic design for airfoils and wings is to improve the performance of the lifting surfaces, e.g., by minimizing the drag. We consider here two approaches, the classical inverse design approach that finds the surface which produces desired pressure distributions, and the direct mathematical optimization based on local parameter searches, that is usually enabled by fast gradient computation, for example, by the adjoint method. The hybrid approach is to combine both of them. Each approach has its own pros and cons. In this chapter the approaches are assessed by application to the design of transonic RAE2822 airfoil and ONERA M6 wing.

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Notes

  1. 1.

    This section is adapted from [5, 18].

  2. 2.

    www.foi.se/en/Customer--Partners/.../Edge1/Edge/.

  3. 3.

    http://www.aiaa.org/.

  4. 4.

    1 drag count is defined as 104 drag coefficient; 1 lift count is defined as 103 lift coefficient.

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Acknowledgements

Part of the computations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at PDC Centre for High Performance Computing (PDC-HPC)

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Authors and Affiliations

  1. Royal Institute of Technology (KTH), 10044, Stockholm, Sweden

    Mengmeng Zhang & Arthur William Rizzi

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  1. Mengmeng Zhang
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  2. Arthur William Rizzi
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Correspondence to Mengmeng Zhang .

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Editors and Affiliations

  1. Engin. Optimization & Modeling Cent, Reykjavik University, Reykjavik, Iceland

    Slawomir Koziel

  2. College of Engineering, Iowa State University, Ames, Iowa, USA

    Leifur Leifsson

  3. School of Science and Technology, Middlesex University, London, United Kingdom

    Xin-She Yang

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Zhang, M., Rizzi, A.W. (2016). Assessment of Inverse and Direct Methods for Airfoil and Wing Design. In: Koziel, S., Leifsson, L., Yang, XS. (eds) Simulation-Driven Modeling and Optimization. Springer Proceedings in Mathematics & Statistics, vol 153. Springer, Cham. https://doi.org/10.1007/978-3-319-27517-8_4

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