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Shuliang Cao

Researcher at Tsinghua University

Publications -  52
Citations -  1797

Shuliang Cao is an academic researcher from Tsinghua University. The author has contributed to research in topics: Impeller & Centrifugal pump. The author has an hindex of 24, co-authored 51 publications receiving 1287 citations.

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Theoretical model of energy performance prediction and BEP determination for centrifugal pump as turbine

TL;DR: In this article, a flowrate-based iteration method is proposed to determine the best efficiency point (BEP) under turbine mode, and the predicted results by theoretical model are compared with experimental measurements and numerical simulations.
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Hydrodynamic design of rotodynamic pump impeller for multiphase pumping by combined approach of inverse design and CFD analysis

TL;DR: In this paper, a combined approach of inverse method and direct flow analysis is presented for the hydrodynamic design of gas-liquid two-phase flow rotodynamic pump impeller.
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Numerical study on characteristics of unsteady flow in a centrifugal pump volute at partial load condition

TL;DR: In this article, the detailed flow field and cavitation effect in the centrifugal pump volute at partial load condition was elucidated by using a computation fluid dynamics framework combining the re-normalization group k-e turbulence model and the mass transport cavitation model.
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Cavitation–Vortex–Turbulence Interaction and One-Dimensional Model Prediction of Pressure for Hydrofoil ALE15 by Large Eddy Simulation

TL;DR: In this paper, the cavitating flow around the asymmetric leading edge (ALE) 15 hydrofoil is investigated through large eddy simulation with the modified Schnerr-Sauer cavitation model, which considers the effect of noncondensable gas.
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Optimization design of a reversible pump–turbine runner with high efficiency and stability

TL;DR: In this article, a multiobjective optimization design system, including a 3D inverse design, computational fluid dynamics, design of experiment, response surface methodology, and multi-objective genetic algorithm, is introduced and applied to the design of a middle-high-head pump-turbine runner.