Optimization Design of Exhaust Hood Based on Elliptical Basis Functions Neural Network Model
The optimal Latin hypercube experimental design method was used to build the sample database,the approximate model based on the elliptical basis functions neural network model and the global optimization of multi-island genetic algorithm were employed to develop a fully automatic optimization design system.Taking the maximization of static pressure recovery coefficient as the optimization goal,the system was applied to optimize the exhaust hood diffuser guide ring profile in the aerodynamic design process.The results show that the initial angle of the guide ring has the most significant impact on the performance of the exhaust hood.The performances of the diffuser and the collector after optimization are improved,the static pressure recovery coefficient of the exhaust hood is increased by 7.91％,and the total pressure loss coefficient is reduced by 5.98％.The improvement is the most significant for the THA conditions.Under the condition of THA,the enhancement in the static pressure recovery coefficient is 13.45％and the decrement in the total pressure loss coefficient is 10.44％.It means that the optimization system is effective and feasible for the aerodynamic design of the steam turbine low-pressure exhaust hood.
NETL
NSTL
万方数据
维普
