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Slip Factor Correction in 1-D Performance Prediction Model for PaTs

Department of Mechanics, Mathematics and Management (DMMM), Polytechnic University of Bari, 70125 Bari, Italy
Author to whom correspondence should be addressed.
Water 2019, 11(3), 565;
Received: 29 December 2018 / Revised: 12 March 2019 / Accepted: 13 March 2019 / Published: 19 March 2019
(This article belongs to the Special Issue Insights on the Water–Energy–Food Nexus)


In recent years, pumps operated as turbines (PaTs) have been gaining the interest of industry and academia. For instance, PaTs can be effectively used in micro hydropower plants (MHP) and water distribution systems (WDS). Therefore, further efforts are necessary to investigate their fluid dynamic behavior. Compared to conventional turbines, a lower number of blades is employed in PaTs, lowering their capability to correctly guide the flow, hence reducing the Euler’s work; thus, the slip phenomenon cannot be neglected at the outlet section of the runner. In the first part of the paper, the slip phenomenon is numerically investigated on a simplified geometry, evidencing the dependency of the lack in guiding the flow on the number of blades. Then, a commercial double suction centrifugal pump, characterized by the same specific speed, is considered, evaluating the dependency of the slip on the flow rate. In the last part, a slip factor correlation is introduced based on those CFD simulations. It is shown how the inclusion of this parameter in a 1-D performance prediction model allows us to reduce the performance prediction errors with respect to experiments on a pump with a similar specific speed by 5.5% at design point, compared to no slip model, and by 8% at part-loads, rather than using Busemann and Stodola formulas. View Full-Text
Keywords: PaT; slip phenomenon; performance prediction; OpenFOAM; CFD PaT; slip phenomenon; performance prediction; OpenFOAM; CFD

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Capurso, T.; Stefanizzi, M.; Pascazio, G.; Ranaldo, S.; Camporeale, S.M.; Fortunato, B.; Torresi, M. Slip Factor Correction in 1-D Performance Prediction Model for PaTs. Water 2019, 11, 565.

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