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
