Understanding the expected performance of large-scale solar ponds from laboratory-scale observations and numerical modeling

Suárez, Francisco; Ruskowitz, Jeffrey A.; Childress, Amy E.; Tyler, S. W.

doi:10.1016/j.apenergy.2013.12.005

Cited by 37 publications

(14 citation statements)

References 45 publications

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“…Even when the difference between T Hi and T Co depends on the value of the effectiveness, the highest T L always agrees with the highest T Co and with the highest useful energy. The optimum z L was found to be 2.57 m, from a total depth of 3.67 m and a brine volume of 85,237 m 3 . This depth produces the highest temperature in the LCZ (namely 68.5°C, as shown in Figure 6b) and in the outlet of the heat exchanger cold stream (52.5°C), delivering 933 kW of useful energy.…”

Section: Thermal Behavior Of a Single Sgspmentioning

confidence: 99%

“…The total area of the SGSP field can be distributed using solar ponds with uniform or variable areas (Figure 3). For the case of uniform area, A uniform i is calculated using equation (3). For the case of variable area, A variable i is estimated using equation (4).…”

Section: Configuration In Parallelmentioning

confidence: 99%

“…SGSPs are water bodies that capture and accumulate solar energy for long time periods [2][3][4][5][6]. These are artificially stratified by dissolving salts with different concentrations to form three characteristic zones ( Figure 1): the upper convective zone (UCZ), the non-convective zone (NCZ) and the lower convective zone (LCZ), which is also known as the storage zone.…”

Section: Introductionmentioning

confidence: 99%

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Constructal design of salt-gradient solar pond fields

González

Amigó

Lorente

et al. 2016

Int. J. Energy Res.

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SUMMARYSalt-gradient solar ponds (SGSPs) are water bodies that capture and accumulate large amounts of solar energy. The design of an SGSP field has never been analyzed in terms of studying the optimal number of solar ponds that must be built to maximize the useful energy that can be collected in the field, or the most convenient way to connect the ponds. In this paper, we use constructal design to find the optimal configuration of an SGSP field. A steady-state thermal model was constructed to estimate the energy collected by each SGSP, and then a complementary model was developed to determine the final temperature of a defined mass flow rate of a fluid that will be heated by heat exchangers connected to the solar ponds. By applying constructal design, four configurations for the SGSP field, with different surface area distribution, were evaluated: series, parallel, mixed series-parallel and tree-shaped configurations. For the study site of this investigation, it was found that the optimal SGSP field consists of 30 solar ponds of increasing surface area connected in series. This SGSP field increases the final temperature of the fluid to be heated in 22.9%, compared to that obtained in a single SGSP. The results of this study show that is possible to use constructal theory to further optimize the heat transfer of an SGSP field. Experimental results of these configurations would be useful in future works to validate the methodology proposed in this study.

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Section: Thermal Behavior Of a Single Sgspmentioning

confidence: 99%

Section: Configuration In Parallelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Constructal design of salt-gradient solar pond fields

González

Amigó

Lorente

et al. 2016

Int. J. Energy Res.

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“…Toffolon et al (2015) recently showed how a minimal model with two parameters is already able to characterize differences in transport between sharp interfaces and unstable regions in a thermohaline staircase. Extending the k-model of SWASH with a parameterization that accounts for these distinct regions could yield a large improvement in properly representing turbulence on proper locations and times.…”

Section: Turbulence Modelmentioning

confidence: 99%

“…For example, double-diffusive processes like thermohaline staircasing have been successfully modelled in lakes (Schmid et al, 2003), although these systems are generally modelled with analytical or empirical formulations (Kelley et al, 2003;Schmid et al, 2004;Arnon et al, 2014). Other known numerical modelling studies consider double-diffusive convection in monitoring wells (Berthold and Börner, 2008) and the collection of thermal energy in solar ponds (Cathcart and Wheaton, 1987;Giestas et al, 2009;Suárez et al, 2010Suárez et al, , 2014. However, modelling these complex physical processes in shallow waters still imposes a major scientific and computational challenge (Dias and Lopes, 2006).…”

Section: Introductionmentioning

confidence: 99%

An axisymmetric non-hydrostatic model for double-diffusive water systems

2018

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Abstract. The three-dimensional (3-D) modelling of water systems involving double-diffusive processes is challenging due to the large computation times required to solve the flow and transport of constituents. In 3-D systems that approach axisymmetry around a central location, computation times can be reduced by applying a 2-D axisymmetric model set-up. This article applies the Reynolds-averaged NavierStokes equations described in cylindrical coordinates and integrates them to guarantee mass and momentum conservation. The discretized equations are presented in a way that a Cartesian finite-volume model can be easily extended to the developed framework, which is demonstrated by the implementation into a non-hydrostatic free-surface flow model. This model employs temperature-and salinity-dependent densities, molecular diffusivities, and kinematic viscosity. One quantitative case study, based on an analytical solution derived for the radial expansion of a dense water layer, and two qualitative case studies demonstrate a good behaviour of the model for seepage inflows with contrasting salinities and temperatures. Four case studies with respect to doublediffusive processes in a stratified water body demonstrate that turbulent flows are not yet correctly modelled near the interfaces and that an advanced turbulence model is required.

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Comment on “Capabilities and limitations of tracing spatial temperature patterns by fiber‐optic distributed temperature sensing” by Liliana Rose et al.

Suárez

2014

Water Resources Research

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The need of precise thermal measurements at high spatial and temporal resolutions for scientific discovery has pushed the development of fiber-optic distributed temperature sensing (FO-DTS) in geosciences. Since its first appearance in the hydrologic community [Selker et al., 2006a[Selker et al., , 2006b], FO-DTS has been used in numerous environmental and engineering applications [Lutz et al., 2012;Striegl and Loheide, 2012;Krause and Blume, 2013;Su arez et al., 2014] and apparently its use will continue to grow in the future. Researchers have realized that one of the main challenges for successful FO-DTS data collection is to achieve the best calibration setup [Tyler et al., 2009;Su arez et al., 2011;Hausner et al., 2011; van de Giesen et al., 2012]. On this subject, the work of Hausner et al. [2013] provides a valuable clarification that should be useful for future investigations. However, their data show a consistent bias and inconsistencies at almost all the spatial scales that may be due to calibration issues. In this comment, I would like to emphasize that the physical installation (also known as deployment) combined with calibration methodologies are crucial for successful FO-DTS data collection.Rose et al. [2013] used a duplex single-ended configuration and a constant temperature ice bath for calibration purposes. The calibration section passed through this bath at positions 20-40 m and 240-260 m, and they matched the temperatures of those sections at a fixed value that was independently measured with a thermistor. The main issue with this physical setup is that the reference sections have the same (or very similar) temperature. As discussed by Hausner et al. [2011], to estimate the calibration parameters of a FO-DTS trace at least two different temperatures are needed in the reference sections [see Hausner et al., 2011, Figure 1]; otherwise, the system of equations that governs the physics of backscattering inside a fiber-optic cable may not have a unique solution, which could yield erroneous temperature estimations.

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Understanding the expected performance of large-scale solar ponds from laboratory-scale observations and numerical modeling

Cited by 37 publications

References 45 publications

Constructal design of salt-gradient solar pond fields

Constructal design of salt-gradient solar pond fields

An axisymmetric non-hydrostatic model for double-diffusive water systems

Comment on “Capabilities and limitations of tracing spatial temperature patterns by fiber‐optic distributed temperature sensing” by Liliana Rose et al.

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