Optimization of oil slurry pump blades based on non-dominated sorting genetic algorithm-II

The catalyst solid particles transported by the oil slurry pump can cause the impeller wear and operation failure. In the study, the impeller of an oil slurry pump was optimized to reduce its wear rate under the premise of the constant efficiency, with a particle size of 0.3 mm and a concentration of 3%. Plackett–Burman screening experimental design was used for significance analysis, and blade wrap angle, rear cover inlet angle, and blade outlet width were selected as subsequent optimization parameters through sensitivity analysis. The optimal space filling method is used to generate impeller parameter design samples, and the average wear rate and efficiency of each group samples are obtained through numerical simulation. An objective function prediction surrogate model is established based on the Kriging response surface model, and the non-dominated sorting genetic algorithm-II is applied for global optimization to obtain the optimal blade profile. The pressure distribution inside the optimized impeller of the oil slurry pump is more uniform, the turbulent energy at the interface between the impeller and the volute is reduced, the average wear rate of the optimized impeller is reduced by 14.12%, and the efficiency of the pump is improved by 3.05%. Under different flow rates, particle concentrations, and particle sizes, the optimized impeller also improved the external characteristics of the pump and reduced its wear rate.