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Aerodynamic Optimization Design of Last Stage Long Blade for Steam Turbine Using Self-Adaptive Differential Evolutionary Algorithms and RANS Solutions

机译:自适应微分进化算法和RANS求解汽轮机末级长叶片气动优化设计

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High performance of the last stage long blade plays an important role on the aerodynamic performance of low pressure cylinder for steam turbines. Aerodynamic optimization design of the last stage long blade for the maximization total-total isentropic efficiency with constraints of mass flow rate and leaving velocity using self-adaptive differential evolution algorithm is presented in this work. The aerodynamic performance of last stage is evaluated using three-dimensional Reynolds-Averaged Navier-Stokes(RANS) computations. Six two-dimensional airfoils along the span and three controlling points for the radial foil of blade using B-Spline functions are used to parameterize the three-dimensional profiles of the stator and rotor blade of the last stage, respectively. Self-adaptive differential evolution algorithms is developed to optimize the maximization total-total isentropic efficiency of last stage. The results show that the total-total isentropic efficiency of the optimized last stage is higher 1.68% than that of the referenced design. Furthermore, the aerodynamic performance of the five stages low pressure cylinder with three extractions coupled with the optimized last stage and referenced design is analyzed and compared. The detailed flow field and aerodynamic parameters of the optimized last stage are also illustrated.
机译:末级长叶片的高性能对蒸汽轮机低压缸的空气动力学性能起着重要作用。这项工作提出了最后阶段长叶片的气动优化设计,利用自适应微分进化算法最大化总等熵效率,并限制了质量流量和离开速度。使用三维雷诺平均Navier-Stokes(RANS)计算评估最后阶段的空气动力学性能。使用B样条函数,沿着翼展的六个二维翼型和叶片径向箔的三个控制点分别用于参数化最后一级的定子叶片和转子叶片的三维轮廓。开发了自适应差分演化算法,以优化最后阶段的最大化总等熵效率。结果表明,优化后阶段的总等熵效率比参考设计的总等熵效率高1.68%。此外,分析并比较了具有三个抽气口的五级低压气缸的空气动力学性能,以及优化的最后一级和参考设计。还说明了优化后阶段的详细流场和空气动力学参数。

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