• A novel Angled Funnel-shaped Fin geometry is integrated with hybrid and penta-hybrid nanofluids in a triplex-tube heat exchanger for enhanced thermal storage. • Advanced optimization techniques (Taguchi, RSM, and ANOVA) are used to improve solidification performance in latent heat thermal energy storage systems (LHTESS). • An Artificial Neural Network (ANN) model is developed to accurately predict solid fraction, average temperature, and total energy during PCM solidification. • The Full Solidification Time (FST) was significantly reduced: from 6265 s in Case 1 and 5760 s in Case 13 to 4670 s in the optimized case, marking improvements of 28.6% and 18.92%, respectively. • Incorporating radiative heat transfer decreases FST by an additional 22.69% and further improves thermal performance. • Use of penta-hybrid nanofluid yields a 0.64% further reduction in FST due to enhanced thermal conductivity. This study presents a numerical investigation to enhance the solidification performance of latent heat thermal energy storage systems (LHTESS) by integrating a novel Angled Funnel-shaped Fin geometry with hybrid and penta-hybrid nanofluids in a triplex-tube heat exchanger (TTHX). The combined use of the Taguchi method, Response Surface Methodology (RSM), and Analysis of Variance (ANOVA) enables systematic optimization of fin dimensions and angular orientations to accelerate solidification. To further support performance assessment, an Artificial Neural Network (ANN) is developed to predict solid fraction, average temperature, and total energy, showing excellent agreement with numerical results and strong generalization capability. The optimized design realized considerable performance enhancement, decreasing the Full Solidification Time (FST) from 6265 s and 5760 s in Case 1 and Case 13 to 4670 s decreasing by 28.6% and 18.92%, respectively. The optimal case improves freezing performance by maximizing the effective heat transfer area and conductive pathways, which reduces thermal resistance and accelerates solidification within the PCM. Besides, the average temperature at 7000 s was reduced by 1.58% and 0.83%, and the total energy was reduced by 1.51% and 0.83% for the optimized case in comparison to Case 1 and Case 13, respectively. The model incorporation of radiative heat transfer for the situation added to the enhanced outcomes; the increase in the parameter from Rd = 0 to Rd = 1 decreased FST by 22.69%, and at the same time, the average temperature and total energy were reduced by 1.81%. Additionally, the application of the penta-hybrid nanofluid in comparison to the hybrid nanofluid resulted in a 0.64% additional FST caused by the increase in thermal conductivity, proving the enhancements. The result of the study provides insightful value pertinent to enhancing the efficiency and response time for LHTESS systems. The results are mainly applicable to cold energy storage systems and HVAC cooling applications, where rapid and efficient low-temperature energy storage is essential.
Mahboobtosi et al. (Sun,) studied this question.