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首页> 外文会议>ASME Turbo Expo: Turbomachinery Technical Conference and Exposition >ADJOINT-BASED MULTIDISCIPLINARY, MULTIPOINT OPTIMIZATION OF A RADIAL TURBINE CONSIDERING AERODYNAMIC AND STRUCTURAL PERFORMANCES
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ADJOINT-BASED MULTIDISCIPLINARY, MULTIPOINT OPTIMIZATION OF A RADIAL TURBINE CONSIDERING AERODYNAMIC AND STRUCTURAL PERFORMANCES

机译：基于伴随的多学科，考虑空气动力学和结构性能的径向涡轮机的多点优化

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This paper presents a multidisciplinary adjoint-based design optimization of a turbocharger radial turbine for automotive applications. The aim is to improve the total-to-static efficiency of the turbine while keeping mechanical stresses below a predefined limit. The search for the optimal design is accomplished using an efficient Sequential Quadratic Programming algorithm considering additional aerodynamic and manufacturing constraints. The aerodynamic performance of the wheel is evaluated by a Reynolds-Averaged Navier-Stokes solver, whereas the maximum stresses in the material are predicted by a Finite Element Analysis tool. The design gradients required by the optimizer are computed with the adjoint approach which provides sensitivity information largely independent of the number of design variables. The results presented in this paper show the clear need to take into account mechanical stresses during optimization, as they are the most restrictive design limitation. However, the gradient-based optimization algorithm is able to effectively keep the stress levels below the critical value while significantly improving the turbine efficiency in a few design cycles.
机译：本文介绍了用于汽车应用的涡轮增压器径向涡轮机的多学科伴随设计优化。目的是提高涡轮机的总静态效率，同时保持机械应力低于预定限度。考虑额外的空气动力学和制造限制，使用高效的顺序二次编程算法来完成对最佳设计的搜索。车轮的空气动力学性能由雷诺平均的Navier-Stokes求解器评估，而通过有限元分析工具预测材料中的最大应力。优化器所需的设计梯度通过伴随方法计算，该伴随方法在很大程度上独立于设计变量的数量。本文提出的结果表明，清楚地需要在优化期间考虑机械压力，因为它们是最严格的设计限制。然而，基于梯度的优化算法能够有效地保持低于临界值的应力水平，同时显着提高了几个设计周期中的涡轮机效率。

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