In this study, the objective of the optimization of a double-suction pump is the maximization of its hydraulic efficiency. The optimization is performed, by means of the modeFRONTIER optimization platform, in steps. At first, by means of a DOE (Design of Experiments) strategy, the design space is explored, using a parameterized CAD representation of the pump. Suitable metamodels (surrogates or Response Surfaces), which represent an economical alternative to the more expensive 3D CFD model, are built and tested. Among different metamodels, the evolutionary design, radial basis function and the stepwise regression models seem to be the most promising ones. Finally, the stepwise regression model, trained on a set of 200 designs and constructed with only five the most influential input design parameters, was chosen as a potentially applicable metamodel.

Optimization of a single-stage double-suction centrifugal pump

MORGUT, MITJA;NOBILE, ENRICO
2017-01-01

Abstract

In this study, the objective of the optimization of a double-suction pump is the maximization of its hydraulic efficiency. The optimization is performed, by means of the modeFRONTIER optimization platform, in steps. At first, by means of a DOE (Design of Experiments) strategy, the design space is explored, using a parameterized CAD representation of the pump. Suitable metamodels (surrogates or Response Surfaces), which represent an economical alternative to the more expensive 3D CFD model, are built and tested. Among different metamodels, the evolutionary design, radial basis function and the stepwise regression models seem to be the most promising ones. Finally, the stepwise regression model, trained on a set of 200 designs and constructed with only five the most influential input design parameters, was chosen as a potentially applicable metamodel.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2899562
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