Integrated optimization method for transonic turbine based on direct free-form deformation and prescreening differential evolutionary optimizer

Mingsheng Chen, Jiang Chen, Hang Xiang, Yi Liu and Yixuan Guo

Energy, 2024, vol. 291, issue C

Abstract: With the increased load of turbine stages, shock waves and secondary flow influence the performance of turbines more and more significantly. Aiming at improving the aerodynamic efficiency of transonic turbines, an integrated aerodynamic optimization platform for turbines has been established. The aerodynamic shape of the flow path and blades is simultaneously parametrized by a directly manipulated free-form deformation (DFFD) method, and the optimization is conducted via a data-driven differential evolutionary algorithm. Furthermore, a prescreening strategy is introduced to enhance the convergence speed of the optimizer. The TTM-stage is selected as the research object. The result shows that the turbine isentropic efficiency at the design point increases from 90.45 % to 91.94 % after optimization. The main reasons for aerodynamic performance enhancement are the weakening of shock waves and the reduction of separation regions. As a comparison, another two optimization cases are carried out. One optimizes the blades individually with the same methods and configurations, and the other optimizes the blades and flow path simultaneously without the prescreening strategy. The optimized isentropic efficiency in the latter two cases is 91.31 % and 90.92 %, whichis 0.63 % and 1.02 % lower than the first optimization result, respectively. This shows the effectiveness of the proposed optimization method for turbine performance improvement.

Keywords: Aerodynamic optimization; Transonic turbine; Directly manipulated free-form deformation; Differential evolutionary algorithm; Prescreening strategy (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:291:y:2024:i:c:s0360544224000148

DOI: 10.1016/j.energy.2024.130243

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