大膨胀比向心涡轮多学科优化设计及敏感性分析

向心涡轮内部流动复杂，功率密度大且结构限制严，因此，向心涡轮的设计必须考虑到气动、强度、结构等多学科间的耦合问题。采用多学科优化策略是提升向心涡轮气动效率和安全可靠性的一种可行途径。基于向心涡轮结构特点，发展了通用的向心涡轮三维参数化造型方法。耦合多目标优化算法和向心涡轮三维参数化方法，建立了向心涡轮多目标多学科优化设计体系。以频率为约束，以提高总静效率、降低叶根最大应力为优化目标，开展了向心涡轮的多学科优化设计。优化后，在避开所有危险共振频率的前提下，就单一性能指标而言，涡轮级的总静效率最高可提高1.35%，叶根最大当量应力最高可降低12.54%。进一步，对设计空间开展了敏感性分析，揭示了对性能指标影响显著的设计变量，阐明了关键设计变量对性能指标的影响机制。

Multi-Disciplinary Optimization and Sensitivity Analysis of a Large-Expansion-Ratio Centripetal Turbine

With complex internal flow, high power density and strict structural constraints, the design of a centripetal turbine needs to consider the strong coupling between multiple disciplines such as aerodynamics, strength, and structure. The adoption of multi-disciplinary optimization strategy is thereby a feasible way to enhance the aerodynamic efficiency and reliability of the centripetal turbine. According to the structural features of the centripetal turbine, this paper develops a universal 3-D parameterized modeling method for the centripetal turbine. Coupling the multi-objective optimization algorithm and the parameterization method, a multi-objective and multi-disciplinary optimization platform is established for the centripetal turbine. With the frequency taken as constraints, a multi-disciplinary optimization is carried out for the centripetal turbine to improve the total-to-static efficiency and reduce the maximum stress of the blade root. After optimization, for each performance parameter, the total-to-static efficiency of the turbine stage is improved by 1.35% and the maximum equivalent stress of the blade root is reduced by 12.54%, with all the dangerous resonant frequencies avoided. Furthermore, a sensitivity analysis of the design space is carried out to identify the design variables that have a significant impact on the performance indicators and to elucidate the underlying mechanism of the key design variables on the performance indicators.