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Multiobjective Optimization Approach to Multidisciplinary Design of a Three-dimensional Transonic Compressor Blade

机译:三维跨音速压气机叶片多学科设计的多目标优化方法

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An automatic multiobjective optimization approach to multidisciplinary design of turbomachinery blades is proposed in this paper. Based on this approach, an algorithm named Multiobjective Differential Evolution (MDE) is introduced as an optimizer to find the Pareto solution sets of the multidisciplinary design problem. A typical multiobjective function has been applied to demonstrate the performance of the presented multiobjective optimization algorithm. The Non-uniform B-Spline method is adopted to parameterize the turbomachinery blade profiles. The aerodynamic performance of design blade candidates is predicted by using a three-dimensional Reynolds-Averaged Navier-Stokes (RANS) solution. The blade stresses and vibration frequencies are evaluated by means of a finite element analysis coupled with the surface pressure of blades obtained from CFD calculation.To validate the optimization capability of the multiobjective optimization algorithm, the multidisciplinary design of a typical transonic compressor blade, NASA Rotor 37, is conducted. The blade is optimized for the maximization of the isentropic efficiency and the minimization of the maximum stresses with constraints on mass flow rate, total pressure ratio, and dynamic frequencies. The Pareto solutions are obtained from the multiobjective optimization. Based on the analysis of the design objectives between the Pareto designs and reference design, it is indicated that the overall performance of the optimized designs is improved. The results demonstrate that the presented multiobjective optimization algorithm has a potential in blade performance optimization and it is a promising method for the multidisciplinary design of turbomachinery blades.
机译:提出了一种自动多目标优化的涡轮机械叶片多学科设计方法。基于这种方法,引入了一种称为多目标差分进化(MDE)的算法作为优化程序,以查找多学科设计问题的Pareto解集。一个典型的多目标函数已被应用于演示所提出的多目标优化算法的性能。采用非均匀B样条方法对涡轮机械叶片轮廓进行参数化。通过使用三维雷诺平均Navier-Stokes(RANS)解决方案,可以预测设计叶片候选的空气动力学性能。叶片应力和振动频率通过有限元分析以及通过CFD计算获得的叶片表面压力进行评估。 为了验证多目标优化算法的优化能力,对典型的跨音速压缩机叶片NASA转子37进行了多学科设计。叶片经过优化,以实现等熵效率的最大化和最大应力的最小化,并限制了质量流量,总压力比和动态频率。帕累托解是从多目标优化中获得的。根据帕累托设计和参考设计之间的设计目标分析,表明优化设计的整体性能得到了改善。结果表明,所提出的多目标优化算法在叶片性能优化中具有潜力,是涡轮机械叶片多学科设计的一种有前途的方法。

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