An Integrated Design and Optimization Approach for Radial Inflow Turbines—Part I: Automated Preliminary Design
Source abstract
Abstract
An integrated design and optimization approach was developed for radial inflow turbines, which consists of two modules, an automated preliminary design module, and a flexible three-dimensional multidisciplinary optimization module. In this paper, the first module about the automated preliminary design approach was presented in detail and validated by the experimental data. The approach employs a genetic algorithm to explore the design space defined by the loading coefficient, flow coefficient, and rotational speed. The aim is to obtain the best design scheme with high aerodynamic performance under specified constraints and to reduce the dependency on human experiences when designing a radial inflow turbine. The validation results show that the present approach is able to get the optimal design and alleviate the dependence on the designer’s expertise under specified constraints at the preliminary design stage. Furthermore, the optimization results indicate that using the present optimization approach the total-to-static efficiency of the optimized T-100 radial inflow turbine can be increased by 1.0% under design condition and the rotor weight can be decreased by 0.35 kg (26.7%) as compared with that of the original case.
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Research context
OpenAlex topics: Turbomachinery Performance and Optimization · Thermodynamic and Exergetic Analyses of Power and Cooling Systems · Advanced Thermodynamic Systems and Engines
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Shaanxi Engineering Laboratory of Turbomachinery and Power Equipment, Institute of Turbomachinery, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Collaborative Innovation Center of Advanced Aero-Engine, Beihang University, Beijing 100191, China
China Shipbuilding New Power Co., Ltd., Beijing 100097, China
Funding
Specialized Research Fund for the Doctoral Program of Higher Education of China
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