Melting Of Phase Change Material Research Articles

Thermal effect of the anisotropic metal foam on the melting performance of phase change material: A pore-scale study

Recently, metal foams have been attractive in reinforcing the heat storage process of phase change materials (PCMs) beneficial from their high thermal conductivity, interconnected structure, and large specific surface. Nevertheless, the melting of PCM is not uniform caused by convective heat transfer, so it cannot be sufficiently accelerated by a traditional isotropic metal foam. In this study, we numerically investigated the melting performance of PCM in isotropic and anisotropic metal foams. Results illustrated that the X-anisotropic structure can more efficiently enhance the melting performance as compared to the isotropic original metal foam, but the Z-anisotropic structure suppresses it. Moreover, the X-anisotropy-0.5 shows the fastest melting, its complete melting time is significantly reduced by 7.99 % compared with the original model, and its heat storage power is 8.68 % higher than the original one. Instead, the Z-anisotropic models prolong the complete melting time by 11.10 % ˗ 28.55 %. It is owing that the anisotropic structure would promote the heat transfer along one direction but suppress its vertical direction. This article provides a feasible routine to accelerate the melting of metal foam-based PCMs, thus improving the heat storage power of the latent heat thermal energy storage system.

Multi-objective optimization of L-shaped fins in rectangular phase change energy storage units based on genetic algorithm

Phase change energy storage technology holds immense potential in the field of energy storage, and enhancing the efficiency of energy storage systems has long been a focal point of industry attention. This study aims to optimize the design of an L-shaped fin structure to improve the melting rate of the phase change material (PCM) within a rectangular phase change energy storage unit and enhance the overall system performance. Through the utilization of numerical simulations and the response surface method (RSM), the influence of fin design parameters - specifically, the length and thickness of the main segment and the length and thickness of the branch segment - on the energy storage per unit mass (Em) and energy storage efficiency (Pt) of the energy storage unit is evaluated. The results reveal that the length of both the main and branch segments of the L-shaped fin significantly impacts the melting rate of the PCM, whereas the thickness of these segments has a comparatively lesser effect. Additionally, when the length of the main segment reaches a sufficient value, increasing the length of the branch segment effectively addresses the challenge of PCM melting difficulties at the bottom of the rectangular phase change cavity caused by natural convection. The Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is employed for the multi-objective optimization of the L-shaped fin shape, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with entropy weighting is applied for decision-making to determine the optimal solution. Notably, when the weights of Em and Pt are set at 44.9 % and 55.1 % respectively, the overall performance of the energy storage unit is optimized. The Pareto-optimal decision solution exhibits a significant improvement of nearly threefold in Pt compared to the case without fins, while the reduction in Em is only 5.24 %. This design approach presents a novel perspective for determining fin parameters in phase change energy storage devices and is expected to drive advancements in phase change energy storage technology.

Melting Behavior Effect of MXene Nanoenhanced Phase Change Material on Energy and Exergy Analysis of Double and Triplex Tube Latent Heat Thermal Energy Storage

Abstract The impacts of melting behavior on the thermal performance of triple tube thermal energy storage (TT-TES) and double tube thermal energy storage (DT-TES) systems employing cetyl alcohol and 3% v/v. MXene nano-enhanced PCM (NEPCM) are compared and numerically evaluated in this work. For both the DT-TES and TT-TES systems, the following were investigated in connection to melting time: system efficiency, discharged energy, heat transfer rate, exergy destruction, entropy generation number, exergetic efficiency, melting fraction, and melting temperature contours. In addition, the effect of Stefan, Rayleigh, and Nusselt numbers on Fourier numbers are compared for the DT-TES and TT-TES systems with MXene NEPCM. MXene-based nano-enhanced PCM melting in TT-TES displayed 6.53% more Stefan number than cetyl alcohol. DT-TES with pure cetyl alcohol phase change material (PCM) consumes 0.4% more energy at 7800 s than MXene NEPCM. Pure melting of MXene-based nano-enhanced PCM in a TT-TES had 4.16% higher storage exergy than cetyl alcohol. The entropy generation number of pure melting of MXene-based nano-enhanced PCM in TT-TES is 7.93% lower than that of cetyl alcohol. Pure melting of MXene-based nano-enhanced PCM in TT-TES reduces storage energy by 1.95% over cetyl alcohol. Pure cetyl alcohol has 76.99% optimal system efficiency at 5400 s melting time and MXene NEPCM 77.04% at 4800 s in DT-TES. The charging temperature for pure cetyl alcohol PCM in TT-TES is 0.7% lower than in DT-TES. Furthermore, pure melting of MXene-based nano-enhanced PCM in a TT-TES has 1.95% lower storage energy than cetyl alcohol. For a given volume of MXene-based nano-enhanced cetyl alcohol PCM, melting occurs more rapidly in a TT-TES system.

Modeling the thermal behavior of multifunctional syntactic foams containing phase change materials for heat management applications

AbstractSyntactic foams are lightweight porous composites obtained by the addition of hollow glass microspheres (HGMs) to a polymer matrix. This work experimentally and numerically investigates the thermal behavior of epoxy‐based syntactic foams with enhanced multifunctionality produced by incorporating microencapsulated phase change materials (PCMs) as functional fillers, providing thermal energy storage and temperature stabilization due to its large latent heat of melting. Foams are fabricated using varying ratios of HGMs (0–40 vol%) and PCM (0–40 vol%) to achieve tuned densities and thermal properties with a total filler content of up to 40 vol%. A one‐dimensional numerical heat transfer model based on the enthalpy method is presented to simulate the thermal behavior of these materials. The model accurately incorporates the specific heat and thermal conductivity of the foam components, as well as the latent heat absorption during PCM melting (up to 68 J/g). The model is experimentally validated by demonstrating good agreement with the measurements of transient temperature profiles during heating tests on the foam samples. The validated tool is then leveraged to model the thermal response of the foams under a sinusoidally varying heat source, similar to the possible real applicative scenarios. These results can help optimize foam compositions balancing energy storage density, heat transfer properties, and structural support for lightweight energy storage systems. Potential applications include high‐efficiency thermal management in battery packs, electronic cooling, solar energy storage, and sustainable temperature‐controlled buildings.Highlights Foams with 0–40 vol% PCM and 0–40 vol% HGM show up to 68 J/g latent heat. 1D numerical model accurately captures thermal conductivity and PCM phase change. Validated model simulates thermal response under sinusoidal heat, optimizing foam composition. Foams act as thermal reservoirs, maintaining up to 5°C lower surface temperatures than epoxy.

Cycle performance analysis of hybrid battery thermal management system coupling phase change material with liquid cooling for lithium-ion battery module operated at high C-rates

High performance battery thermal management system (BTMS) is urgently needed to satisfy the severe cooling demand of battery modules operated at high C-rates during continuous charging-discharging cycles. Hybrid BTMS coupling phase change material (PCM) with liquid cooling is a promising solution which attracts great attention in recent years. Here, cycle performance of the hybrid system is analyzed in detail via comparison with the pure PCM system to examine its reliability and demonstrate its superiority during continuous 3C-charging and 4C-discharging cycles. Effects of PCM melting temperature are studied and RT44HC is found a suitable PCM choice with appropriate melting temperature. Analysis of the first three cycles is proved important and basically sufficient as system thermal behavior stabilizes afterwards. Further, interacting mechanisms of expanded graphite (EG) content and battery distance on system cooling performance are elucidated and their possible combinations satisfying temperature requirements of battery module in both temperature rise and temperature uniformity are presented. Optimal combination of EG content and battery distance is 3 % and 3 mm. Effects of coolant velocity are also investigated and suitable velocity for the optimized hybrid system is set at 0.01 ms−1 to achieve balance between cooling performance and auxiliary energy cost.

Battery thermal management system by employing different phase change materials with SWCNT nanoparticles to obtain better battery cooling performance

Maintaining a stable temperature within a battery is essential for optimizing the performance of battery thermal management systems. Phase change materials (PCMs) have demonstrated potential in achieving this stability. This study investigates the use of single-walled carbon nanotubes (SWCNTs) dispersed in three PCMs with varying fusion temperatures to regulate the temperature of a lithium-ion battery (LIB) during discharge, a common scenario in electric vehicles. A Computational Fluid Dynamics (CFD) approach was utilized to simulate the liquid-solid transition of the PCMs, incorporating buoyancy forces in the liquid phase surrounding the LIB. The study examined the effects of different C-rates (1, 2, and 3), SWCNT volume fractions (0, 2, and 4 %), and three types of PCMs (RT27, RT35, and RT58) across multiple simulation scenarios to evaluate their impacts on LIB temperature and PCM melting fraction. Results indicate that nano-enhanced PCMs, which exhibit superior convection effects in the liquid phase, significantly enhance battery cooling performance. Specifically, at a C-rate of 1, using a 4 % volume fraction of nanoparticles in the PCM reduces the battery temperature by an average of 4.138 K compared to cases without nanoparticles. Additionally, while nanoparticles are generally reported to have a minor effect on cooling and melting processes, this study reveals that considering the beneficial effects of SWCNTs and the physical properties of the selected PCMs, the cooling performance of LIBs improves by 4.69 percentage points for the scenario with a C-rate of 3, RT58, and ɸ = 0.02. In this particular case, the melting process is more pronounced in the top half of the battery, where the increased velocity magnitude of the melted region contributes to enhanced battery cooling.

Enhanced thermal management strategy for supercapacitors using phase change materials: A numerical investigation

The integration of phase change materials (PCMs) presents a promising possibility for enhancing the thermal management of supercapacitors (SCs), which are vital components in various energy storage systems. This research focuses on investigating the thermal behavior of SCs with integrated PCM, employing finite element method (FEM) simulations to solve the transient thermal problem. Through a comparative analysis at various time instants, the transient thermal response of SCs is examined, shedding light on the efficacy of PCM-based thermal management strategies. Moreover, parametric studies are conducted to investigate the influence of PCM key characteristics, like melting temperature and layer thickness on the SC thermal response. Additionally, the impact of enhanced PCM thermal conductivity is explored by integrating high-conductive short carbon fibers (CF) within the PCM matrix. This investigation encompasses various PCM melting points, allowing for a comprehensive understanding of the interplay between PCM properties and SC thermal response. The results indicate that a notable decline in the highest temperatures of the SC can be achieved, leading to a reduction of about 9 °C depending on the PCM melting temperature and the improved thermal conductivity. The obtained results emphasize the effectiveness and practical feasibility of the proposed thermal management strategy. The modeling approach presented provides a robust tool with significant efficiency in reducing computational time for analyzing the thermal behavior of large models, as the utilization of the homogenization technique notably decreases the computational time. The findings of this study not only provide insights into optimizing PCM-based thermal management strategies for SCs but also contribute to advancing the design and performance of energy storage systems by addressing crucial thermal challenges.

Melting performance improvement of phase change materials with thermal energy storage unit using nanoparticles

The world is facing two major problems today, as imbalance of supply and demand of the energy and the continues deterioration of the environment. Latent thermal energy storage with phase change material plays a vital rule in resolving this problem. The current study investigates the numerical simulation of phase change material with novel fins configuration in the triplex-tube storage unit. But their low thermal conductivity is the main problem by affecting the energy storage. To enhance the heat transfer rate within the system, novel longitudinal triangular and traditional rectangular fins with a combination of hybrid nanoparticles (Cu-TiO2) are employed. In summary, utilizing novel fins to improve heat transfer rate in conjunction with nanoparticles is highly effective for improving the phase change material melting process in thermal energy storage systems. The usage of nanoparticles speeds up the melting rate 33.5%- Case A, 20%-Case B, 19.4%-Case C, and 18% for Case D. Moreover, when compared to rectangular-shaped fins, the use of longitudinal triangular -shaped fins accelerates the PCM melting rate. For instance, the melting rate in Case C (fins with longitudinal triangular form) is higher than in Case F (fins with a rectangle shape).

Melting and heat management of phase change material using smart ternary-hybrid coolant

This research investigates the effectiveness of using a smart ternary-hybrid nanofluid to enhance the melting rate and convective behavior of electrically conducting tin (Sn) in a rectangular enclosure under the influence of a uniform magnetic field. The enclosure has adiabatic vertical walls with hot and cold temperatures on the bottom and top walls. The finite element method (FEM) is used to solve the governing equations with appropriate boundary conditions using Galerkin's weighted residual approach. The study focuses on applying tin as the phase change material (PCM), with the highest temperature of 508 K, the lowest temperature of 503 K, and the melting interface temperature of 505 K. To enhance the heat transfer performance, tin-based ternary (graphene (G), silicon carbide (SiC), and nickel (Ni)) hybrid smart coolant is applied into the system. To investigate the mechanism of the melting and convective thermal transfer process, the results of the present study are reported with time for various values of the magnetic field (Ha) and solid concentration of ternary hybrid nanoparticle (ϕ). This study represents the streamlines, isothermal lines, melting interface, melting fraction, and heat transfer for the above-mentioned parameters. The results show that increasing the magnetic field reduces the rate of thermal transport by 38.96 % at t = 4000s. However, at a particular time of 2500s, increasing the solid volume fraction of nanoparticles enhances the melting fraction by approximately 8.34 %. Two regression equations are derived for the Nusselt number and melting fraction, with multiple response variables. This article improves understanding of natural convective heat transport during phase change processes for various coolants in different engineering applications.

CRYOMOVE: Cold chain real-time management of vaccine delivery using PCM and deep learning

Vaccines are temperature-sensitive biological products that can become ineffective or even hazardous if exposed to temperatures outside the recommended range. Therefore, it is crucial to maintain the cold chain during the transportation and storage of vaccines in order to ensure that they arrive at their destination in optimal condition. Vaccines are typically transported and stored in containers lined with Phase Change Material (PCM) to maintain a specific temperature range (usually lower than the ambient temperature). Firstly, we have simulated the melting of PCM at three distinct external temperatures using ANSYS Fluent software in order to forecast the Melt Fraction (MF) vs. time curve for each of these temperatures. The external temperature consistently undergoes dynamic changes. Running a simulation each time the temperature shifts is impractical due to its time and data-intensive nature. Consequently, we adopted a more efficient approach by training a simple Artificial Neural Network (ANN) based on simulation data. This ANN is designed to learn and predict the MF versus time curve for any given external temperature. Real-time temperature data from the vaccine box is transmitted to the cloud. Subsequently, the machine learning model operates on the cloud to predict the remaining time for the PCM to melt. This predictive analysis is performed recursively every 10 min to account for dynamic fluctuations in external temperatures, providing continuous updates on the time remaining for PCM meltdown. This is then conveyed to the cold chain managers to take preventive measures if the external conditions are harsh and there is a chance for vaccines to get ruined because of the temperature. This same approach can be extended to other applications beyond vaccine delivery such as food storage and transportation, pharmaceuticals, and more.

Statics Performance and Heat Dissipation Evaluation of Lattice Structures Prepared by Laser Powder Bed Fusion.

This paper address the performance optimization of the battery heat sink module by analyzing the lattice structure of the battery heat sink module through in-depth modeling and simulation, and combining the laser powder bed fusion (LPBF)-forming technology with mechanical and corrosion resistance experiments for a comprehensive study. It is found that the introduction of the lattice skeleton significantly improves the thermal conductivity of the phase change material (PCM), realizing the efficient distribution and fast transfer of heat in the system. At the same time, the lattice skeleton makes the heat distribution in the heat exchanger more uniform, improves the utilization rate of the PCM, and helps to maintain the stability of the cell temperature. In addition, the melting of PCM in the lattice heat exchanger is more uniform, thus maximizing its latent heat capacity. In summary, by optimizing the lattice structure and introducing the lattice skeleton, this study successfully improves the performance of the battery heat dissipation system, which provides a strong guarantee for the high efficiency and stable operation of the battery, and provides new ideas and references for the development of the battery heat dissipation technology.

Enhancing the phase change material based shell-tube thermal energy storage units with unique hybrid fins

The poor thermal conductivity of phase change material (PCM) has limited its application to thermal energy storage system. The present work aims to improve the performance of PCM in a vertical shell-tube energy storage unit through unique hybrid fins. The enthalpy-porosity approach is used to numerically investigate the phase change phenomenon. Based on the straight and spiral fin results, the novelty designs of double side spiral fin and hybrid fins, i.e. spiral/straight hybrid fin and straight/spiral hybrid fin, are proposed to further optimize the PCM charging process. The effects of different fin structure, hybrid fin proportion and spiral fin angle on the liquid fraction, temperature and average thermal energy storage rate are discussed. The fin structures can reduce the melting time of PCM up to 100% compared to the no-fin case. Although double side spiral fin outperforms the straight fin for the PCM melting behavior, the hybrid fin configurations shows the best enhancement, especially for the straight/spiral hybrid fin. The optimal fin design for the straight/spiral hybrid fin case is that with 0.7 fin proportion and 180° spiral angle, with up to 11.8% reduction of the melting time compared to the designs of other fin proportions and spiral angles. This work demonstrates the potential of this unique hybrid fin to be integrated with PCM for efficient thermal energy storage.

Expression of Concern for article entitled “Investigation of heat transfer, melting and solidification of phase change material in battery thermal management system based on blades height”

Expression of Concern for article entitled “Investigation of heat transfer, melting and solidification of phase change material in battery thermal management system based on blades height”

A novel design of lithium-polymer pouch battery pack with passive thermal management for electric vehicles

This study investigates the thermal characteristics of a lithium polymer pouch battery thermal management system using phase change material (PCM) during the discharge. The research provides a detailed discussion of various factors influencing the system. The novelty aspect of this study involves evaluating thermal changes in the battery at 40 °C through hot soaking experiments comparing with both PCM-integrated modules and without PCM modules. The study further aims to identify the optimal PCM for both normal and high ambient conditions. Thermal parameters, including maximum temperature Tmax, average temperature Taverage and thermal gradient ΔT were evaluated at 25 °C and hot soaking performance at 40 °C temperature during discharge was analysed. Simulation were conducted to compare module behavior, especially at high-temperature conditions. Furthermore, a thorough examination of PCM melting and solid-phase transitions at high temperatures were performed that significantly impact the cooling performance of the PCM system. Our findings reveal that expanded graphite PCMs offers effective thermal performance with observed improvement of 27 %. Therefore, we recommend employing EG26 and EG28 PCMs for real-world application electric vehicle battery pack systems.

Magnetically- regulated close contact melting for high-power-density latent heat energy storage

Rapid melting of solid-liquid phase change materials (PCMs) is critical to the high-power-density latent heat energy storage and efficient thermal management. The pressure-enhanced close contact melting is seen as a promising method because of the suppressed heat transfer resistance between the heating surface and the melt front during thermal charging, but it remains a key challenge how to tactfully apply external pressure for a practical device. Herein, we present a magnetically-regulated close contact melting strategy for rapid melting of PCMs from the perspective of the practical application. In this method, a PCM and a permanent magnet are contained inside a highly thermally conductive vessel, and the magnet regulated by another one can push the solid PCM toward the heating surface. Consequently, the superheated molten PCM can be instantly removed from the heating surface due to the magnetic force so as to achieve the suppressed thermal resistance. The temperature-control performance of paraffin wax is evaluated under various applied external forces and heat loads. Experimental results indicate that the heating surface temperature can be controlled near the melting temperature of PCM even under a relatively high heating flux. With applying the external pressure of 900 Pa, the average heat transfer resistance is reduced to lower than 4.5 × 10−4 K·m2·W−1. Finally, a closed thermal management device is fabricated and measured by using a graphite vessel to encapsulate the magnet and the PCMs such as paraffin and low-melting-point alloy. This device demonstrates good recyclability for repeated thermal charging/discharging. Our work provides a new method to develop the practical thermal management device based on pressure-enhanced close contact melting.

Analysis of the influence of asymmetric V-shaped fins on the melting of phase change materials in latent heat storage units

Improving the melting performance of latent heat storage devices is highly important for achieving efficient utilization of thermal energy. To achieve this goal, this paper proposes an innovative thermal storage unit with asymmetric V-shaped fins. The influence of structural parameters including eccentricity, fin angle, height and shape on the melting process of phase change materials is analysed. The results show that compared with concentric tubes without eccentricity, when the eccentricity is increased to the point where the bottom fins are in contact with the outer tube, the total melting time is shortened by 33.56%, and the average heat storage rate is increased by 32.95%. At the same time, increasing the angle and height of the top branch fins can strengthen the natural convection in the heat storage unit and shorten the total melting time by 13.54%. It is worth noting that changing the upper-side branch fin parameters has little effect on the melting process. In addition, when the shape of the branch fins constituting the V-shaped fin changes from rectangular to trapezoidal, the total melting time decreases by 3.11%. In summary, the use of asymmetric V-shaped fins can improve the melting performance and heat storage performance of eccentric heat storage units, and changing the fin shape can further shorten the total melting time and increase the average heat storage rate.

Parametric analysis of system performance and cost of heating systems with heat pump and latent thermal energy storage

This paper presents a parametric analysis examining the impact of phase change material (PCM) melting temperature, latent thermal energy storage (LTES) volume, and solar collectors’ surface area on the performance and costs of heating systems integrating a heat pump and LTES by using dynamic system simulations. The computational models, implemented in TRNSYS software, and the numerical procedure were validated by comparing the numerical results with experimental measurements. The computational models represent the entire heating systems and thus consider the mutual interaction of heat production, distribution and automatic regulation system as well as a building which represent the heat load, in transient boundary conditions. Two main system designs with different LTES roles were considered – a system in which the role of the LTES is to provide more favorable operating conditions and a system in which the LTES role is to store the heat on a sufficiently high temperature to be used directly for heating. System performance was analyzed in terms of the share of renewable energy in total delivered energy, power consumption, stored energy in LTES, seasonal performance factor, average solar collector efficiency and total annual costs. The results showed that, regarding the system in which LTES was used as a heat source for the heat pump, a better overall performance and lower costs were observed in systems with PCMs with melting temperatures in range between 19 and 29 °C, compared to systems with PCMs with melting temperatures outside this range. For system in which the heat from the LTES was used directly for heating, the highest values of system performance criteria and the lowest cost were achieved with the PCM of 54 °C melting temperature. Almost all of the considered system performance criteria and total costs were higher when the LTES volume and solar collector surface area were larger as well.

Predicting the PCM-incorporated building's performance using optimized linear kernel and tree-based machine learning methods

The devising of a precise machine learning-based energy consumption prediction model holds significant importance for taking effective decisions during the early stages of phase change material (PCM) incorporated building design to reduce energy consumption. Few researchers have developed prediction models for estimating the consumption of energy in PCM incorporated buildings. However, there is a need to develop the best-performing machine learning-based prediction model, which is less complex, involve a lower number of hyperparameters, and has a greater ability to generalize hidden patterns among the dependent and independent variables. To address the above shortcomings, the linear kernel and tree model-based prediction models were formulated for PCM-incorporated buildings located in eight cities of subtropical highland climate, considering the variations in their hyperparameters. The evaluation and validation of the formulated models for prediction were performed utilizing several statistical metrics. Test results substantiated that the ensemble-boosted tree-based prediction model (EBT20) exhibited superior efficacy in estimating the energy consumption for PCM-integrated building, having an average R2 > 0.93, NMBE <4 %, and CV-RMSE <8 %. The developed model showed less complexity and better generalization ability at the optimized values of ensemble boosted tree hyperparameters, which are as follows: minimum leaf size = 32, number of learners = 99, and learning rate = 0.1. From comprehensive evaluation conducted to evaluate the interpretability of the prediction model, it was found that the building orientation and PCMs melting temperature are the most influential parameters for achieving energy savings of up to 33 % in the selected climate zone.

Enhancing melting performance in multi-tube latent heat exchangers: Investigating the effect of inner tube number and arrangement

The latent heat energy storage system holds promising application prospects in the field of energy. However, the critical bottleneck remains the melting speed of phase change materials (PCMs). In this study, the melting dynamics of PCM within a triplex-tube heat exchange system are investigated, focusing on the effects of varying the number and arrangement of inner tubes. The system performance with four, five, six, and seven inner tubes is compared, revealing a decrease in melting time with an increasing number of inner tubes. However, excessive numbers do not yield more significant enhancement. A novel arrangement scheme is proposed, recommending six inner tubes. Additionally, the effects of inner tube spacing, upper angle and lower angle are explored. Increasing these parameters initially decreases melting time but then exhibits a reverse trend. Specifically, appropriate spacing enhances coverage area, expediting rapid connectivity of melting areas and thereby augmenting natural convection. While an increase in the upper angle delays PCM melting in the upper half, optimal arrangement enhances lower half PCM melting. Balancing melting rates of three difficult-to-melt areas in the lower half with proper lower angle achieves optimal performance. Compared with the base case, the proposed arrangement with the tube spacing of 40 mm, upper angle of 92°, and lower angle of 62° reduces melting time by 44.8 %. These findings provide a theoretical and experimental foundation for enhancing PCM-based energy storage system performance, offering valuable insights for engineering applications.

Optimization of fin arrangement in solar thermal storage devices and convolutional neural network modeling

Solar energy, a renewable and eco-friendly source, faces challenges in aligning energy production with storage durations. Phase change materials (PCMs) effectively tackle this issue, yet their poor thermal conductivity limits solar thermal storage device performance. Conventional solutions involve adding fins, but limited volume compromises overall heat storage capacity. Our study enhances device performance by rearranging fins while maintaining the same area. The H/R = 0.5 fin arrangement with equal spacing significantly improves heat storage, reducing total melting time by 54.31% with a higher entropy value. Further, arranging five fins, predominantly in the lower part, shortens PCM melting time without compromising upper material melting, enhancing device temperature uniformity. Utilizing computed data, we trained a Convolutional Neural Network (CNN) model, maintaining a maximum error within 5%, with an actual maximum error of only 1.56%. The efficacy of CNN in addressing prediction challenges is noteworthy, showcasing improved solar thermal storage device performance.