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An airfoil optimization technique for wind turbines

机译：风力涡轮机的翼型优化技术

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摘要

Optimization algorithms coupled with computational fluid dynamics are used for wind turbines airfoils design. This differs from the traditional aerospace design process since the lift-to-drag ratio is the most important parameter and the angle of attack is large. Computational fluid dynamics simulations are performed with the incompressible Reynolds-averaged Navier-Stokes equations in steady state using a one equation turbulence model. A detailed validation of the simulations is presented and a computational domain larger than suggested in literature is shown to be necessary. Different approaches to parallelization of the computational code are addressed. Single and multiobjective genetic algorithms are employed and artificial neural networks are used as a surrogate model. The use of artificial neural networks is shown to reduce computational time by almost 50%.
机译：结合计算流体动力学的优化算法用于风力涡轮机翼型设计。这与传统的航空航天设计过程不同，因为升阻比是最重要的参数，迎角也很大。使用一方程湍流模型，使用稳态时不可压缩的雷诺平均Navier-Stokes方程进行计算流体动力学模拟。给出了仿真的详细验证，并且显示了大于文献中建议的计算范围是必要的。解决了使计算代码并行化的不同方法。采用单目标和多目标遗传算法，并将人工神经网络用作替代模型。事实证明，使用人工神经网络可将计算时间减少近50％。

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  • 来源
    《Applied Mathematical Modelling》 |2012年第10期|p.4898-4907|共10页
  • 作者

    A.F.P. Ribeiro; A.M. Awruch; H.M. Gomes;

  • 作者单位

    Graduate Program in Mechanical Engineering, Federal University of Rio Crande do Sul, Av. Osvaldo Aranha, 99, Porto Alegre, RS, Brazil;

    Graduate Program in Mechanical Engineering, Federal University of Rio Crande do Sul, Brazil;

    Graduate Program in Mechanical Engineering, Federal University of Rio Crande do Sul, Brazil;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    computational fluid dynamics; genetic algorithms; artificial neural networks;

    机译：计算流体动力学;遗传算法;人工神经网络;

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