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Multi-objective shape optimization of transonic airfoil sections using swarm intelligence and surrogate models

  • Industrial Application
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Abstract

In this article, the optimization problem of designing transonic airfoil sections is solved using a framework based on a multi-objective optimizer and surrogate models for the objective functions and constraints. The computed Pareto-optimal set includes solutions that provide a trade-off between maximizing the lift-to-drag ratio during cruise and minimizing the trailing edge noise during the aircraft’s approach to landing. The optimization problem was solved using a recently developed multi-objective optimizer, which is based on swarm intelligence. Additional computational intelligence tools, e.g., artificial neural networks, were utilized to create surrogate models of the objective functions and constraints. The results demonstrate the effectiveness and efficiency of the proposed optimization framework when applied to simulation-based engineering design optimization problems.

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Authors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, Old Dominion University, 238 Kaufman Hall, Norfolk, VA, 23529-0247, USA

    Miltiadis Kotinis & Amit Kulkarni

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  1. Miltiadis Kotinis
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  2. Amit Kulkarni
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Correspondence to Miltiadis Kotinis.

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Kotinis, M., Kulkarni, A. Multi-objective shape optimization of transonic airfoil sections using swarm intelligence and surrogate models. Struct Multidisc Optim 45, 747–758 (2012). https://doi.org/10.1007/s00158-011-0719-7

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  • DOI: https://doi.org/10.1007/s00158-011-0719-7

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