CFD-ML analysis of finned pipe hybrid PCM systems for enhanced cold energy storage

This study investigates a hybrid Phase Change Material system for enhanced thermal energy storage in refrigerated transportation, bridging gaps in Latent Thermal Energy Storage applications. A dual phase change material configuration of RT27 and n-octadecane, integrated with liquid cooling and cooling pipe fins, is analyzed using Computational Fluid Dynamics simulations. The study optimizes thermal management in refrigerated trucks by varying the number of fins. Key performance indicators include temperature distribution, liquid fraction, and melt fraction reduction. Results show that the hybrid system with eight fins achieves a 6.55% reduction in peak temperature for n-octadecane compared to the base case. The melting fraction of RT27 is reduced by 26.51%, and n-octadecane melting is reduced by 71.93% with eight fins. Machine learning models, specifically Levenberg-Marquardt algorithm and Scaled Conjugate Gradient, predict melt fractions with high accuracy, with R-values of 0.933 and 0.941, respectively, for the base case. The findings highlight the effectiveness of hybrid cooling systems, demonstrating significant improvements in thermal energy storage and refrigeration performance.