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Gradient Span Analysis Method: Application to the Multipoint Aerodynamic Shape Optimization of a Turbine Cascade

机译:梯度跨度分析方法:在涡轮叶栅多点气动形状优化中的应用

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摘要

This paper presents the application of the gradient span analysis (GSA) method to the multipoint optimization of the two-dimensional LS89 turbine distributor. The cost function (total pressure loss) and the constraint (mass flow rate) are computed from the resolution of the Reynolds-averaged Navier-Stokes equations. The penalty method is used to replace the constrained optimization problem with an unconstrained problem. The optimization process is steered by a gradient-based quasi-Newton algorithm. The gradient of the cost function with respect to design variables is obtained with the discrete adjoint method, which ensures an efficient computation time independent of the number of design variables. The GSA method gives a minimal set of operating conditions to insert into the weighted sum model to solve the multipoint optimization problem. The weights associated to these conditions are computed with the utopia point method. The single-point optimization at the nominal condition and the multipoint optimization over a wide range of conditions of the LS89 blade are compared. The comparison shows the strong advantages of the multipoint optimization with the GSA method and utopia-point weighting over the traditional single-point optimization.
机译:本文介绍了梯度跨度分析(GSA)方法在二维LS89涡轮分配器多点优化中的应用。成本函数(总压力损失)和约束条件(质量流量)是根据雷诺平均Navier-Stokes方程的分辨率计算的。惩罚方法用于用无约束问题代替约束优化问题。优化过程由基于梯度的拟牛顿算法控制。成本函数相对于设计变量的梯度是通过离散伴随方法获得的,从而确保了与设计变量数量无关的高效计算时间。 GSA方法给出了可插入到加权和模型中的最小操作条件集,以解决多点优化问题。与这些条件相关的权重通过乌托邦点法计算。比较了标称条件下的单点优化和LS89刀片在各种条件下的多点优化。比较表明,与传统的单点优化相比,使用GSA方法进行的多点优化和乌托邦点加权具有明显的优势。

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