Parametric design and multiple objective intelligent optimization of marine nuclear turbine aerothermodynamics under variable conditions - Lei Zhang; Guobing Chen; Yu-Ang Shi; LuoTao Xie (Scientific Reports)
Abstract Our goal is to improve the aerothermodynamics performance of the marine nuclear-powered turbine and control the exhaust humidity of the blade grid, thereby improving the operating efficiency and power of the turbine and ensuring safety. We propose a method for parameterized reconstruction of steam turbine blade profiles based on their geometric parameters using a coordinate equation developed based on the third-order Bezier curve. By combining the blade parameterized reconstruction method with a Kriging approximation model and a multi-objective genetic algorithm (GA), we developed an optimized system for thermodynamic performance in turbines. The optimization objective was the cascade core thermal parameters of steam turbine under multiple operating conditions. The design parameters were the geometric parameters of the parameterized blade profile. Based on the calculation results of wet steam non-equilibrium condensation flow of steam turbine, the optimization method and process of multi-objective thermodynamic performance of steam turbine blades based on Kriging model were proposed. Then, we executed parameterized reconstruction of a Dykas planar cascade and a steam turbine 3D cascade to achieve multi-parameter, multi-condition design optimization of planar and 3D cascades. The analysis results showed that after optimizing the turbine cascade under different operating conditions, the outlet humidity decreased by 6.1–8.9%, the maximum droplet diameter decreased by 11.4–15.8%, and the isentropic efficiency increased by 0.6–0.9%. Using the proposed novel method, the isentropic efficiency and stage power of steam turbine cascades at variable operating conditions were enhanced, thermodynamic parameters (e.g., velocity, temperature, and pressure) were more homogeneously distributed, and overload condition sites showed more significant improvements. Thus, the proposed method achieved multi-condition, multi-constraint thermodynamic performance design optimization of wet steam turbine blades, thereby providing insights for intelligent design optimization and operation of wet steam turbine cascades.