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Research Papers

Optimization, Numerical, and Experimental Study of a Propeller Pump as Turbine

[+] Author and Article Information
Shahram Derakhshan

School of Mechanical Engineering,
Iran University of Science & Technology,
Narmak 16846, Tehran, Iran
e-mail: shderakhshan@iust.ac.ir

Nemat Kasaeian

School of Mechanical Engineering,
Iran University of Science & Technology,
Narmak 16846, Tehran, Iran

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received May 19, 2013; final manuscript received December 18, 2013; published online February 28, 2014. Assoc. Editor: S. O. Bade Shrestha.

J. Energy Resour. Technol 136(1), 012005 (Feb 28, 2014) (7 pages) Paper No: JERT-13-1153; doi: 10.1115/1.4026312 History: Received May 19, 2013; Revised December 18, 2013

Micro hydropower station is one of the clean choices for offgrid points with available hydropotential. The challenging in this type of energy production is the high capital cost of the installed capacity that is worse for low-head micro hydropower stations. Turbine price is the main problem for this type of energy production. In this research, a simple machine has been introduced instead of conventional propeller turbines. The key is using an axial pump as a propeller turbine. In the present research, a propeller pump was simulated as a turbine by numerical methods. Computational fluid dynamics (CFD) was adopted in the direct and reverse modes performance prediction of a single propeller pump. To give a more accurate CFD result, all domains within the machine control volume were modeled and hexahedral structured mesh was generated during CFD simulation. Complete performance curves of its pump and turbine modes were acquired. For verification of the numerical results, the machine has been tested in an established test ring. The results showed that a propeller pump could be easily run as a low-head turbine. In the next, the goal was to optimize the geometry of the blades of axial turbine runner which leads to maximum hydraulic efficiency by changing the design parameters of camber line in five sections of a blade. The efficiency of the initial geometry was improved by various objective functions and optimized geometry was obtained by genetic algorithm and artificial neural network to find the best efficiency of the turbine. The results showed that the efficiency is improved by more than 14%. Indeed the geometry has better performance in cavitation.

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References

Figures

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Fig. 1

Applications of various pumps as turbines

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Fig. 2

Propeller pump impeller

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Fig. 3

The numerical model of propeller pump

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Fig. 4

Blade structured grid

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Fig. 5

3D generated grid of the machine

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Fig. 7

Low-head micro turbine test rig established in laboratory

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Fig. 8

Method of measuring the shaft torque of PAT

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Fig. 9

Optimization algorithm

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Fig. 10

Comparison between pump head experimental and numerical results

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Fig. 11

Comparison between pump efficiency experimental and numerical results

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Fig. 12

Comparison between pump power experimental and numerical results

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Fig. 13

Comparison between PAT head experimental and numerical results

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Fig. 14

Comparison between PAT efficiency experimental and numerical results

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Fig. 15

Comparison between PAT power experimental and numerical results

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Fig. 16

Evolution of objective function during optimization

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Fig. 17

Comparison between PAT efficiency experimental, numerical, and optimization results

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