A natural convection conjugate heat transfer of Nano-Encapsulated Phase Change Materials (NEPCMs) in an inclined blocked square enclosure

Abdi, Mohamed; Chaib, Khaled; Menouer, Abdelfettah; Benferhat, Slimane

doi:10.1080/10407782.2022.2153769

Cited by 6 publications

(1 citation statement)

References 32 publications

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“…Recent developments in the field of microencapsulated phase change materials have focused on improving their performance, durability, and cost effectiveness. Researchers have been exploring various promising solutions, focusing on the heat transfer [9], and their integration in thermal energy storages [10]. However, there are also some significant disadvantages for using latent heat storage, which include:…”

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confidence: 99%

Subcooling Effect on PCM Solidification: A Thermostat-like Approach to Thermal Energy Storage

et al. 2023

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Choosing the right phase change material (PCM) for a thermal energy storage (TES) application is a crucial step in guaranteeing the effectiveness of the system. Among a variety of PCMs available, the choice for a given application is established by several key factors, e.g., latent heat, stability, and melting point. However, phenomena such as subcooling—for which PCM cools in a liquid state below its solidification point—can lead to a reduction in the amount of energy stored or released, reducing the TES overall effectiveness, and also in some inaccuracies when modeling the problem. Thus, understanding the effects of subcooling on PCM performance is crucial for modeling and optimizing the design and the performance of TES systems. To this end, this work analyzes the PCM discharging phase in a cold thermal energy storage coupled to a chiller system. A first conduction-based predictive model is developed based on enthalpy–porosity formulation. Subcooling phenomena are encompassed through a control variable formulation, which takes its cue from the operation of a thermostat. Then, thermal properties of the PCM, i.e., the phase change range and specific heat capacity curve with temperature, are evaluated by using differential scanning calorimetry (DSC), in order to derive a second predictive model based on these new data, without including subcooling, for the sake of comparison with the first one. Experimental results from the storage tank confirm both model reliability and the fact that the PCM suffers from subcooling. Between the two numerical models developed, the first one that considers subcooling proves it is able to predict with satisfactory accuracy (RMSE < 1 °C) the temperature evolution on different tank levels.

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confidence: 99%