Second Law Optimization of a PCM Based Latent Heat Thermal Energy Storage System with Tree Shaped Fins

Abstract

The aim of this paper is to perform a thermodynamic optimization of a Y shaped fin design used to improve thermal performance of a latent heat thermal energy storage (LHTES) unit. The investigation is performed through a CFD model that takes into account the thermal behavior of the system. Temperature and phase fields are obtained to characterize the heat transfer phenomenon and to compute the entropy generation rate within the system. Global entropy generation and energy flux are adopted as objective functions to perform a shape optimization of the Y shaped fins with angles and branches lengths that can vary freely. The optimization results indicate that a higher energy transfer is achieved by a fin configuration with long secondary branches with an orientation angle of 30°. This design allows one to increase PCM solidification rate of about 30%. Furthermore, Y-shaped fins allow to increase the exergy flux released by the PCM, thus Second-law efficiency is not affected although entropy generation increases. This work represents the first detailed thermodynamic optimization of a system involving an unsteady process. This aspect is particularly important since a clear tendency of many energy systems is toward transient operation, thus design optimization methods should evolve accordingly.

Entropy generation analysis as a design tool—A review

“…Wang et al [116] Turbomachinery Numerical optimization of a centrifugal fan through EGA Inadoli and Sciubba [118,119] Turbomachinery Design improvement of turbomachinery designs through EGA Zuniga et al [121] Heat sinks in electronic devices Fins geometrical parameters optimized through the analysis of local entropy generation Guelpa et al [125] Latent heat energy storage system First use of local entropy generation for the design improvement for an unsteady state system Sciacovelli et al [129] Latent heat energy storage system Fins shape optimization through EGM Datta [131,133] Confined diffusion flames Identification of local entropy generation for a reactive system Jejurkar and Mishra [138] Microcombustor Wall material was selected to achieve optimal second-law performance Sciacovelli and Verda [141][142][143] Solid oxide fuel cells Entropy generation analysis through CFD modelling; Design improvement and shape optimization were performed Ibáñez et al [151,152,155] MHD systems Local entropy generation was identified in channel configurations Caldas and Semiao [159] Radiative systems Local entropy generation due to radiation was formulated Makhanlall et al [164] Solar collector Entropy generation due to radiation and convection was evaluated; effect of tilt angle was investigated system design that allows one to attain an optimal time evolution is sought after, and therefore several designs must be analyzed and their performance compared over a certain time interval. Especially if the boundary conditions are non-stationary, the corresponding computational time required by transient CFD models may become unwieldy.…”

“…However, very few studies about shape optimization through entropy generation minimization are available in the literature and this field is almost uncovered. Sciacovelli et al [129] performed a shape optimization of a latent heat energy storage system through the combined use of a parameterized CFD model and an optimization algorithm. The shape of the fins was optimized with the aim of minimizing the thermodynamic irreversibilities and improving the thermal performance.…”

Energy and exergy performance assessments for latent heat thermal energy storage systems

“…In addition, for any particle fraction, since the viscosity of hydrated salt is higher than that of paraffin wax, the former encounters more exergy destruction than latter [39] Melting point difference between first and last PCM is key for optimum exergy performance [22] Melting temperatures of first and last PCMs should be close to HTF and atmospheric temperatures, respectively, for optimum exergy efficiency [63] Increase in exergy efficiency due to multiple PCMs is not affected by the latent heat of PCM [64] Storage unit dimension Exergy efficiencies increase with increasing the length of the tube during the solidification period of an ice-on-coil thermal energy storage tank [17] The entropy generation increases with decrease in heat transfer surface area [40] The dimensions of the PCM unit are expected to influence the heat transfer mechanism of the phase change process. The solidification of PCM is always governed by conduction heat transfer, which is generally not affected by the unit dimensions [65] The dominance of natural convection is significant only in larger rectangular systems [66] The dominance of natural convection is significant only in larger rectangular units [67] Increasing shell radius reduces the entropy generation number [68] Both energy and exergy efficiency were evaluated for spherical, cylindrical and slab capsule geometries and different operating conditions for the solidification process in encapsulated ice thermal energy storage system. A CFD model has been used to compute global entropy generation while no detail about local irreversibilities [69] Heat exchanger surface enhancement…”

Entropy Generation Analysis of Wildfire Propagation

“…Minimum entropy generation analysis has been applied to thermal insulation problems involving minimum heat transfer at fixed temperature difference and thermal enhancement involving minimum temperature difference to exchange a fixed heat flux [2]. In the literature, there are numerous applications of entropy generation analysis to storage systems [5][6][7], fluid flow within technical devices [8][9][10], engines [11,12], heat exchangers [13,14] and desalination plants [15].…”