This numerical study explores dynamic melting as an enhancement strategy to improve heat transfer in thermal energy storage (TES) systems utilizing phase change materials (PCM) with openings. Optimizing such systems is crucial for advancing renewable energy storage and integration. A 3D model simulates RT35 PCM flowing through a shell-and-tube heat exchanger annulus. The effects of varying PCM inlet slot diameter (2.5–7.5 mm), inlet pressure (1–40 Pa), and inlet/outlet port positioning on melting fraction and temperature distributions are computationally evaluated. Results show that increasing slot diameter from 2.5 mm to 7.5 mm reduces melting time by 13.6 % (from 550 to 475 min). Raising inlet pressure from 10 Pa to 40 Pa cuts melting time by 43.8 % (from 400 to 225 min). However, varying inlet/outlet port positioning has negligible impact. Larger slot diameters and higher pressures produce more homogeneous melting across the radial width. A neural network approach revealed that port diameters around 5.5 mm maximized melting volume fraction at early stages, while increasing port size accelerated melting in later stages. This study provides quantitative data demonstrating that optimizing dynamic melting parameters through the annulus can substantially enhance heat transfer in open PCM-based TES systems. The novelty lies in systematically evaluating the effects of these design parameters on melting behavior and employing artificial intelligence to further analyze parameter interactions
Background: The rapid evolution of Artificial Intelligence (AI) has significantly influenced Education, demonstrating substantial potential to transform traditional teaching and learning methods. AI reshapes teacher-student interactions and the relationship with knowledge. Objective: To analyze the potential benefits, ethical challenges, and limitations of AI in Education based on recent scientific literature, emphasizing the balance between technology and human interaction. Methods: A documentary research approach with a descriptive focus was employed, following the PRISMA protocol for systematic reviews. The search strategy involved analyzing evidence from 18 scientific articles published within the last six years. Results:AI o
... Show MoreAdverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
... Show MoreThe design of coordination compounds with solvent-responsive optical properties remains a central challenge in molecular photonics. Here, we describe the synthesis and full characterisation of a symmetrical tetradentate diamine ligand, 3,3′-((1,2-phenylenebis(azanediyl))- bis(methanylylidene))bis(pentane-2,4-dione) (H₂L), and its neutral square-planar complexes [M(L)] (M(II) = Co, Ni, Cu). The Cu(II) complex crystallised as [Cu(L)]⋅0.5 (pyrazine), adopting a nearly square-planar geometry (τ₄ = 0.06) in the solid state, as confirmed by single-crystal X-ray diffraction. In DMSO solution, UV–Vis spectra revealed reversible axial coordination of two solvent molecules, driving a transformation to a distorted octahedral geometry. Struc
... Show MorePhase change materials are extensively studied for use in low-, mid-, and high-temperature applications due to their melting and solidification temperatures, latent heat, and thermophysical properties. This work aims to explore the energy stored, or released and their duration for the energy storage unit formed of a phase change material surrounding a tube within which a hot or cold, single or Two-Phase fluid flows, serving as a heat source or sink. The 3D axial transient thermal analysis of the energy storage unit is performed using the finite element method via a MATLAB-developed computer program. The effects of single- or Two-Phase fluid flow on temperature distribution, solidification, melting duration, and energy stored within phase ch
... Show MoreThe present study explores numerically the energy storage and energy regeneration during Melting and Solidification processes in Phase Change Materials (PCM) used in Latent Heat Thermal Energy Storage (LHTES) systems. Transient two-dimensional (2-D) conduction heat transfer equations with phase change have been solved utilizing the Explicit Finite Difference Method (FDM) and Grid Generation technique. A Fortran computer program was built to solve the problem. The study included four different Paraffin's. The effects of container geometrical shape, which included cylindrical and square sections of the same volume and heat transfer area, the container volume or mass of PCM, variation of mass flow rate of heat transfer fluid (HTF), and temp
... Show MoreIn this paper, an experimental analysis of conventional air-cooled and microchannel condensers in automotive vapor compression refrigeration cycle concerning heat transfer coefficient and energy using R134a as a refrigerant was presented. The performance of two condensers and cycles tested regarding ambient temperature which it was varied from 40oC to 65oC, while the indoor temperature and load have been set to be 23oC and 2200 W respectively. Results showed that the microchannel condenser has 224 % and 77 % higher refrigerant side and air side heat transfer coefficient respectively than the coefficients of the conventional condenser. Thus, the COP, in case of using the microchannel
... Show MoreThis study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big
... Show MoreThe aim of this work was to capture solar radiation and convert it into solar thermal energy by using a storage material and the heat transfer fluid like oil and water and comparison between them, we used the evacuated tube as a receiver for solar radiation, The results showed that the oil better than water as storage material and the heat transfer fluid and the effective thermal conductivity material and good for power level, rates and durations of charge and discharge cycles.