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Open AccessArticle

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

1
National Research Center of Pumps, Jiangsu University, Zhenjiang 212013, China
2
Mechanical Engineering Department, Wa Polytechnic, Wa, Upper West, Ghana
*
Author to whom correspondence should be addressed.
Processes 2019, 7(5), 246; https://doi.org/10.3390/pr7050246
Received: 4 April 2019 / Revised: 22 April 2019 / Accepted: 24 April 2019 / Published: 27 April 2019
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. View Full-Text
Keywords: multi-objective optimization; artificial neural network; NPSHr prediction; cavitation optimization; CFD multi-objective optimization; artificial neural network; NPSHr prediction; cavitation optimization; CFD
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MDPI and ACS Style

Wang, W.; Osman, M.K.; Pei, J.; Gan, X.; Yin, T. Artificial Neural Networks Approach for a Multi-Objective Cavitation Optimization Design in a Double-Suction Centrifugal Pump. Processes 2019, 7, 246.

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