Energy Reports · 2022 · 125 citations · 36 references
EngineeringMaterials EngineeringMaterials ScienceComputational Heat TransferHeat TransferThermal AnalysisHeat Transfer AnalysisHeat Transfer In FluidsHeat Transfer ModelingMelting Behavior AnalysisThermal DesignThermal Properties Of MaterialsDimensionless Heat Transfer AnalysisFoam StructureHeat Transfer EnhancementHeat Transfer ProcessesHeat Transfer RateMeltingNusselt NumberPhase Change Material Modeling
Improving the heat‑transfer performance of phase‑change materials is essential for efficient latent‑heat thermal energy storage systems. This study investigates how a metal‑foam‑fin hybrid structure and container inclination affect the phase‑change process using numerical simulation. Numerical simulations, validated by an experimental system, compare solid–liquid interfaces, liquid fraction, Fo×Ste, and average Nusselt number for PCM in containers at 0°, 30°, 60°, and 90° with fin, metal‑foam, and hybrid structures, and an artificial neural network predicts liquid fraction and Nusselt number during phase change. The hybrid structure shortens melting time and reduces Fo×Ste by up to 60 % at 90°, while more fins improve heat transfer and lower heat accumulation, though energy‑storage density per unit volume decreases with higher inclination and fin count; the ANN predicts liquid fraction and Nusselt number with MSE ≈ 9.6 × 10⁻⁵ and R² ≈ 0.999.
Improving the heat transfer performance of phase change material (PCM) plays a crucial role in designing efficient latent heat thermal energy storage (LHTES) systems. The purpose of this study is to address and elucidate the effects of the metal foam-fin hybrid structure and the inclination angle on the phase change process by using the numerical simulation method. An experimental system for the validation of the numerical models is established. The solid–liquid phase interfaces, streamlines, liquid fraction (f), the dimensionless time (Fo×Ste), and average Nusselt number (Nu¯) of PCM in the container enclosure at inclination angles of 0°, 30°, 60°, and 90° with six kinds of enhanced heat transfer structures, including fin, metal foam, and metal foam-fin hybrid structures, are compared. Besides, the liquid fraction and Nu¯ during the phase change process are predicted by the artificial neural network (ANN). Results demonstrate that the optimized heat transfer performance of the metal foam-fin hybrid structure could reduce the melting time. In addition, the increase in the number of fins can improve the heat transfer performance and reduce heat accumulation in the top area with the inclination angle increasing. Compared to pure PCM at the inclination angle of 90°, the values of Fo×Ste of metal foam-1 fin and metal foam-5 fins hybrid structures are reduced by 52.69% and 60.02%, respectively. However, the energy storage density per unit volume decreases as a function of the increasing inclination angles and the number of fins within a case. Furthermore, the excellent predictions of f and Nu¯ are obtained by ANN with MSE and R2 of 9.6480 × 10−5, 0.9990 and 0.0150, 0.9937, respectively.
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Ziye Ling, Zhengguo Zhang, Guo-Quan Shi et al. · Renewable and Sustainable Energy Reviews · 2014 · 543 citations