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To solve that problem, an optimization strategy has been designed to widen the high-efficiency range of the double-suction centrifugal pump at design (<jats:italic>Q<\/jats:italic><jats:sub>d<\/jats:sub>) and nondesign flow conditions. An orthogonal experimental scheme is therefore designed with the impeller hub and shroud angles as the decision variables. Then, the \u201cefficiency-house\u201d theory is introduced to convert the multiple objectives into a single optimization target. A two-layer feedforward artificial neural network (ANN) and the Kriging model were combine based on a hybrid approximate model and solved with swarm intelligence for global best parameters that would maximize the pump efficiency. The pump performance is predicted using three-dimensional Reynolds-averaged Navier\u2013Stokes equations which is validated by the experimental test. With ANN, Kriging, and a hybrid approximate model, an optimization strategy is built to widen the high-efficiency range of the double-suction centrifugal pump at overload conditions by 1.63%, 1.95%, and 4.94% for flow conditions 0.8<jats:italic>Q<\/jats:italic><jats:sub>d<\/jats:sub>, 1.0<jats:italic>Q<\/jats:italic><jats:sub>d<\/jats:sub>, and 1.2<jats:italic>Q<\/jats:italic><jats:sub>d<\/jats:sub>, respectively. A higher fitting accuracy is achieved for the hybrid approximation model compared with the single approximation model. A complete optimization platform based on efficiency-house and the hybrid approximation model is built to optimize the model double-suction centrifugal pump, and the results are satisfactory.<\/jats:p>","DOI":"10.1155\/2020\/9737049","type":"journal-article","created":{"date-parts":[[2020,9,26]],"date-time":"2020-09-26T23:31:37Z","timestamp":1601163097000},"page":"1-18","source":"Crossref","is-referenced-by-count":5,"title":["Efficiency-House Optimization to Widen the Operation Range of the Double-Suction Centrifugal Pump"],"prefix":"10.1155","volume":"2020","author":[{"given":"Wenjie","family":"Wang","sequence":"first","affiliation":[{"name":"National Research Center of Pumps, Jiangsu University, Zhenjiang 212013, China"}]},{"given":"Majeed Koranteng","family":"Osman","sequence":"additional","affiliation":[{"name":"National Research Center of Pumps, Jiangsu University, Zhenjiang 212013, China"},{"name":"Department of Mechanical Engineering, Wa Technical University, Wa, 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