Optimization of a direct-acting pressure regulator for irrigation systems based on CFD simulation and response surface methodology

• Published in: Irrigation science Vol. 35; no. 5; pp. 383 - 395
• Main Authors: Zhang, Chen, Li, Guangyong
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2017; Springer Nature B.V
• Subjects: Agriculture; algorithms; Aquatic Pollution; Biomedical and Life Sciences; Climate Change; Computer applications; Computer simulation; Design optimization; dynamic models; Environment; equations; Finite element method; Fluid mechanics; Genetic algorithms; Interactions; Irrigation; Irrigation systems; Layering; Life Sciences; Mathematical models; Optimization; Original Paper; Performance indices; Pressure; Pressure regulators; regression analysis; Response surface methodology; Simulation; Spring; Sustainable Development; Waste Water Technology; Water Industry/Water Technologies; Water Management; Water Pollution Control
• ISSN: 0342-7188; 1432-1319
• DOI: 10.1007/s00271-017-0545-9

A dynamic model of direct-acting pressure regulator was developed using the layering dynamic mesh technique to numerically determine the performance indexes. The validation test of the dynamic model was conducted. The central composite design of the response surface methodology was used to arrange the numerical experiments. Two quadratic polynomial regression equations were fitted for the computational preset pressure ( P set ) and slope of the performance line of the unregulated segment ( η ) data in terms of five variables. The optimization model was established and solved using genetic algorithm in combination with superimposed contour plot approach, which considered maximum achievable η under a certain P set as the object function. Results showed that numerical and measured P set and η agreed within −19.7 and 9.4%, respectively. Effects of geometrical and spring parameters and their interactions on P set and η were successfully revealed. In a comparison between the optimization solution and simulation confirmation results, the relative deviations of P set and η lie within 4.8 and −7.1%. The optimized η for P set of 0.05, 0.07, and 0.1 MPa was improved by 16.5, 8.5, and 13.8%, respectively. The proposed optimization model can be practically applied to design of pressure regulator.