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Research Papers: Alternative Energy Sources

Study of Buoyancy-Driven Flow Effect on Salt Gradient Solar Ponds Performance

[+] Author and Article Information
Shahram Derakhshan

Iran University of Science and Technology,
Tehran 16846-13114, Iran,
e-mail: shderakhshan@iust.ac.ir

Seyedeh Elnaz Mirazimzadeh

Iran University of Science and Technology,
Tehran 16846-13114, Iran
e-mail: mirazimzadeh.elnaz@gmail.com

Syamak Pazireh

Iran University of Science and Technology,
Tehran 16846-13114, Iran
e-mail: syamak.pazireh@gmail.com

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received April 25, 2017; final manuscript received April 25, 2018; published online May 29, 2018. Assoc. Editor: Reza Sadr.

J. Energy Resour. Technol 140(10), 101203 (May 29, 2018) (9 pages) Paper No: JERT-17-1176; doi: 10.1115/1.4040189 History: Received April 25, 2017; Revised April 25, 2018

Salt gradient solar ponds are the ponds in which due to existence of saline and salt gradient layers, lower layers are denser and avoid the natural convection phenomenon to occur so that solar radiation energy can be stored in the lowest zone. In this study, one-dimensional (1D) and two-dimensional (2D) numerical approaches have been implemented to simulate unsteady buoyancy-driven flow of solar ponds. In 1D method, the pond has been investigated in terms of the layers thicknesses so that the variation of temperature is calculated by energy conservation equation. The formulized radiation term was used as energy source term in energy equation. The results of 1D approach were validated with an experimental study and then optimization was carried out to determine the maximum thermal efficiency for an interval of layers height. Since the stability of the solar pond cannot be determined by 1D simulation, a 2D approach was considered to show the stability for different nonconvective zone (NCZ) heights and different salt gradients. In 2D study, in order to investigate hydrodynamic and thermal behavior of saltwater fluid, a numerical approach was used to simulate temperature gradients throughout the pond. The results of 2D numerical method are validated with an experimental data. The effect of linear and nonlinear salt gradient was considered.

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References

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Figures

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Fig. 1

Schematic of a solar pond

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Fig. 2

Temperature distribution along the pond width obtained by 1D simulation on Oct. 1, 1997 and comparison of numerical and experimental data [13]

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Fig. 8

Temperature variation with height of pond at the time 300 (s) (experimental [30] and numerical data)

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Fig. 12

Temperature distribution contours at different times—height of NCZ is 8 mm—stable behavior for linear salt gradient

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Fig. 13

Temperature distribution contours at different times—height of NCZ is 16 mm—stable behavior for linear salt gradient

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Fig. 14

Temperature distribution contours at different times—height of NCZ is 16 mm—unstable behavior for nonlinear salt gradient

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Fig. 9

Temperature variation with height of pond at the time 600 (s) (experimental [30] and numerical data)

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Fig. 3

Temperature distribution along the pond width obtained by 1D simulation on Apr. 1, 1997 and comparison of numerical and experimental data [13]

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Fig. 4

Effect of NCZ layer thickness on the LCV temperature obtained by 1D simulation

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Fig. 5

Effect of NCZ layer thickness on the LCV temperature obtained by 1D simulation

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Fig. 6

Temperature variation with height of pond at the time 120 (s) (experimental [30] and numerical data)

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Fig. 7

Temperature variation with height of pond at the time 180 (s) (experimental [30] and numerical data)

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Fig. 10

Three different salt gradients as input to this study

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Fig. 11

Corresponding temperature distribution along the pond to the input salt gradients of Fig. 10

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