Artificial Neural Networks Approach for a Multi-Objective Cavitation Optimization Design in a Double-Suction Centrifugal Pump

• Published in: Processes Vol. 7; no. 5; p. 246
• Main Authors: Wang, Wenjie, Osman, Majeed Koranteng, Pei, Ji, Gan, Xingcheng, Yin, Tingyun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.05.2019
• Subjects: Accuracy; Algorithms; Angles (geometry); Artificial neural networks; Cavitation; Centrifugal pumps; Design of experiments; Design optimization; Efficiency; Flow velocity; Genetic algorithms; Impellers; Mathematical models; Multiple objective analysis; Neural networks; Orthogonal arrays; Pareto optimization; Simulation; Suction; Turbulence models; Viscosity; United States > US
• ISSN: 2227-9717; 2227-9717
• DOI: 10.3390/pr7050246

Double-suction centrifugal pumps are widely used in industrial and agricultural applications since their flow rate is twice that of single-suction pumps with the same impeller diameter. They usually run for longer, which makes them susceptible to cavitation, putting the downstream components at risk. A fast approach to predicting the Net Positive Suction Head required was applied to perform a multi-objective optimization on the double-suction centrifugal pump. An L32 (84) orthogonal array was designed to evaluate 8 geometrical parameters at 4 levels each. A two-layer feedforward neural network and genetic algorithm was applied to solve the multi-objective problem into pareto solutions. The results were validated by numerical simulation and compared to the original design. The suction performance was improved by 7.26%, 3.9%, 4.5% and 3.8% at flow conditions 0.6Qd, 0.8Qd, 1.0Qd and 1.2Qd respectively. The efficiency increased by 1.53% 1.0Qd and 1.1% at 0.8Qd. The streamline on the blade surface was improved and the vapor volume fraction of the optimized impeller was much smaller than that of the original impeller. This study established a fast approach to cavitation optimization and a parametric database for both hub and shroud blade angles for double suction centrifugal pump optimization design.