Abstract: To enlarge the high efficiency area of the residual heat removal pump (RHRP), an optimization process is proposed based on Kriging model and neighborhood cultivation genetic algorithm (NCGA). 16 design cases containing three main parameters, which are incidence angle ∆β, are angle φ and outlet blade angle β2, are designed by using the Latin hypercube sampling (LHS) methods. The efficiencies are calculated by steady numerical simulation. The efficiencies under the design point 1.0Qd and 1.62Qd are selected as the objective functions. Approximation models between the efficiencies and the parameters are built by Kriging model. The neighborhood cultivation genetic algorithm is applied to optimize the approximation models to obtain the best combination of parameters. The results show that the predicted performance has a good agreement with that of the experiment of the original pump. The efficiencies of the optimal pump are 5.53% and 2.29% higher than those of the original one under 1.0Qd and 1.62Qd, respectively. Meanwhile, the relative velocity distributions are more uniform in the optimal impeller. The optimization method can provide an effective reference to the improvement of pump’s performance.

Key words: impeller, Kriging model, Latin hypercube sampling, neighborhood cultivation genetic algorithm, residual heat removal pump, two-point