Optimization Design and Internal Flow Characteristics Analysis Based on Latin Hypercube Sampling Method

Double-suction centrifugal pumps are ubiquitous in industrial settings and daily life. As energy equipment technology advances, demands for their efficiency and stability continue to rise. This study presents an optimization design approach for such pumps. Employing the Latin cube experimental design method, we optimized five key geometric design parameters of a double-suction centrifugal pump impeller, aiming to maximize efficiency (η). The regression equation yielded predicted impeller efficiency and head of 84.5% and 23.95 m, respectively. Efficiency and head deviations were minimal (0.04% and 2.75%), both within 5%, validating the applicability of the optimization design method combining Latin cube sampling and response surface modeling. The optimized design parameters for the double-suction centrifugal pump are: β_1h = 31.4, β_1s = 15.2, β_2h = 20.2, β_2s = 20.2, φ = 105.1. Numerical simulation results aligned closely with model test data (error < 4%), confirming the accuracy and reliability of the numerical simulation method. The optimized impeller model enhanced pump efficiency by 1.3%, particularly under low flow conditions (improvement > 3%), expanding the pump's efficient operation range. Additionally, the novel Ω (Omega) vortex method effectively captured internal vortex phenomena. Comparative analysis revealed strong static and dynamic interference at the inter-tongue region, dominating pressure pulsation. The optimized model eliminated low-frequency radial force pulsation and reduced force fluctuations under all working conditions. The improved matching between the impeller and chambers led to more uniform and stable flow. This study offers valuable insights for further optimizing double-suction centrifugal pump designs.