Simultaneous efficiency improvement of pump and turbine modes for a counter-rotating type pump-turbine

This article presents a multi-objective optimization to improve the hydrodynamic performance of a counter-rotating type pump-turbine operated in pump and turbine modes. The hub and tip blade angles of impellers/runners with four blades, which were extracted through a sensitivity test, were optimized...

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Main Authors: Jin-Woo Kim, Jun-Won Suh, Young-Seok Choi, Kyoung-Yong Lee, Joon-Hyung Kim, Toshiaki Kanemoto, Jin-Hyuk Kim
Format: Article
Language:English
Published: SAGE Publishing 2016-11-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/1687814016676680
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author Jin-Woo Kim
Jun-Won Suh
Young-Seok Choi
Kyoung-Yong Lee
Joon-Hyung Kim
Toshiaki Kanemoto
Jin-Hyuk Kim
author_facet Jin-Woo Kim
Jun-Won Suh
Young-Seok Choi
Kyoung-Yong Lee
Joon-Hyung Kim
Toshiaki Kanemoto
Jin-Hyuk Kim
author_sort Jin-Woo Kim
collection DOAJ
description This article presents a multi-objective optimization to improve the hydrodynamic performance of a counter-rotating type pump-turbine operated in pump and turbine modes. The hub and tip blade angles of impellers/runners with four blades, which were extracted through a sensitivity test, were optimized using a hybrid multi-objective genetic algorithm with a surrogate model based on Latin hypercube sampling. Three-dimensional steady incompressible Reynolds-averaged Navier–Stokes equations with the shear stress transport turbulence model were discretized via finite volume approximations and solved on a hexahedral grid to analyze the flow in the pump-turbine domain. For the major hydrodynamic performance parameters, the pump and turbine efficiencies were selected as the objective functions. Global Pareto-optimal solutions were searched using the response surface approximation surrogate model with the non-dominated sorting genetic algorithm, which is a multi-objective genetic algorithm. The trade-off between the two objective functions was determined and described with regard to the Pareto-optimal solutions. As a result, the pump and turbine efficiencies for the arbitrarily selected optimum designs in the Pareto-optimal solutions were increased as compared with the reference design.
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spelling doaj.art-7a12d6771930422d9ed8528f14d107222022-12-21T23:01:22ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402016-11-01810.1177/1687814016676680Simultaneous efficiency improvement of pump and turbine modes for a counter-rotating type pump-turbineJin-Woo Kim0Jun-Won Suh1Young-Seok Choi2Kyoung-Yong Lee3Joon-Hyung Kim4Toshiaki Kanemoto5Jin-Hyuk Kim6Thermal & Fluid System R&D Group, Korea Institute of Industrial Technology, Cheonan-si, Republic of KoreaThermal & Fluid System R&D Group, Korea Institute of Industrial Technology, Cheonan-si, Republic of KoreaThermal & Fluid System R&D Group, Korea Institute of Industrial Technology, Cheonan-si, Republic of KoreaThermal & Fluid System R&D Group, Korea Institute of Industrial Technology, Cheonan-si, Republic of KoreaThermal & Fluid System R&D Group, Korea Institute of Industrial Technology, Cheonan-si, Republic of KoreaInstitute of Ocean Energy, Saga University, Saga, JapanThermal & Fluid System R&D Group, Korea Institute of Industrial Technology, Cheonan-si, Republic of KoreaThis article presents a multi-objective optimization to improve the hydrodynamic performance of a counter-rotating type pump-turbine operated in pump and turbine modes. The hub and tip blade angles of impellers/runners with four blades, which were extracted through a sensitivity test, were optimized using a hybrid multi-objective genetic algorithm with a surrogate model based on Latin hypercube sampling. Three-dimensional steady incompressible Reynolds-averaged Navier–Stokes equations with the shear stress transport turbulence model were discretized via finite volume approximations and solved on a hexahedral grid to analyze the flow in the pump-turbine domain. For the major hydrodynamic performance parameters, the pump and turbine efficiencies were selected as the objective functions. Global Pareto-optimal solutions were searched using the response surface approximation surrogate model with the non-dominated sorting genetic algorithm, which is a multi-objective genetic algorithm. The trade-off between the two objective functions was determined and described with regard to the Pareto-optimal solutions. As a result, the pump and turbine efficiencies for the arbitrarily selected optimum designs in the Pareto-optimal solutions were increased as compared with the reference design.https://doi.org/10.1177/1687814016676680
spellingShingle Jin-Woo Kim
Jun-Won Suh
Young-Seok Choi
Kyoung-Yong Lee
Joon-Hyung Kim
Toshiaki Kanemoto
Jin-Hyuk Kim
Simultaneous efficiency improvement of pump and turbine modes for a counter-rotating type pump-turbine
Advances in Mechanical Engineering
title Simultaneous efficiency improvement of pump and turbine modes for a counter-rotating type pump-turbine
title_full Simultaneous efficiency improvement of pump and turbine modes for a counter-rotating type pump-turbine
title_fullStr Simultaneous efficiency improvement of pump and turbine modes for a counter-rotating type pump-turbine
title_full_unstemmed Simultaneous efficiency improvement of pump and turbine modes for a counter-rotating type pump-turbine
title_short Simultaneous efficiency improvement of pump and turbine modes for a counter-rotating type pump-turbine
title_sort simultaneous efficiency improvement of pump and turbine modes for a counter rotating type pump turbine
url https://doi.org/10.1177/1687814016676680
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