基于NSGA-Ⅱ算法的液环泵叶片型线流热特性多目标优化OA

To tackle the problems of substantial energy loss being converted into heat during the opera-tion of liquid-ring pumps,which causes a temperature rise of the medium and consequently leads to a decline in pump performance,the simulation combined with experimental test,the RBF neural network surrogate model and NSGA-Ⅱ genetic algorithm were used to conduct a flow-thermal coupled multi-objective optimization analysis of the liquid-ring pump's blade profile.The results show that the thermal equilibrium state of the flow in the pump startup process lags behind the equilibrium state of the hy-draulic characteristics for a long time,and the source terms contributing to the increase in thermal energy include compression power and dissipation loss terms.The dissipative power is primarily con-centrated on the outer rim of the impeller,the backside of the blade outlet,as well as the inner wall of the casing within the suction and compression zones.The regions with significant compressive power are mainly located in the gas compression zone and the exhaust zone.The prediction errors of the construc-ted thermal-efficiency surrogate model and vacuum-efficiency surrogate model are both within 5％.In the Pareto frontier of multi-objective optimization,the thermal energy of the model with the minimum thermal energy is 13.80％lower than that of the original model,and its blades feature a larger outlet setting angle β2 and a smaller wrap angle φ.The efficiency of the model with optimal efficiency has im-proved by 7.97％compared to the original model,and its blades feature a larger outlet angle β2 and wrap angle φ.The vacuum of the vacuum optimal design is 7.32％higher than that of the original de-sign,and its blades show smaller outlet angle β2,and larger wrap angle φ.With the increase of outlet angle β2 and the decrease of wrap angle φ,the thermal energy gradually decreases,and there is a cer-tain positive correlation between thermal energy and vacuum degree.The research results can provide a certain theoretical support for performance optimization of liquid-ring pumps.