Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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Article Citation Count: 0Numerical Study of Thermal Performance of Silica-aerogel/Paraffin Nanostructure in the Presence of Cuo Nanoparticles: a Molecular Dynamics Approach(Elsevier B.V., 2025) Ali, A.B.M.; Hussein, R.A.; Babadoust, S.; Singh, N.S.S.; Salahshour, S.; Baghaei, S.The rise in air pollution and fuel costs increased the use of various renewable energy options. Currently, scientists face a significant challenge. Finding methods to store energy that can be easily converted is crucial. There is growing interest in using phase change materials for thermal energy storage systems. This interest stems from their ability to conserve energy and reduce air pollution. Silica aerogel effectively maintains the temperature of items over long periods. Phase change materials, recognized for storing thermal energy, are now favored for preserving both hot and cold temperatures. This study aimed to use computer simulations to understand the behavior of silica aerogel/PCM and CuO nanoparticles in a cube. The results show that the nanostructure can achieve a velocity of 0.0086 Å/fs and had a thermal conductivity of 1.85 W/m·K. These findings may have practical applications in heating and cooling systems, energy storage, and the aerospace industry. © 2025 Elsevier B.V.Article Citation Count: 0Modeling the Thermal Performance of Hybrid Paraffin-Air Nanostructure in a Heat Sink: Effect of Atomic Ratio of Al2o3 Nanoparticles(Elsevier Ltd, 2025) Ghanim, W.K.; Rasheed, R.H.; Sadeq, A.S.; Fares, M.N.; Salahshour, S.; Sabetvand, R.This study investigates the effect of varying atomic ratios (1 %, 3 %, 6 %, and 10 %) of Al₂O₃ nanoparticles on the thermal performance of a hybrid paraffin-air nanostructure in a heat sink, using molecular dynamics simulations. The primary objective is to enhance the thermal properties of phase change materials for efficient energy storage, which is crucial for advancing thermal management systems. The purpose is to optimize nanoparticle concentration and assess how altering the atomic ratio of Al₂O₃ nanoparticles can improve thermal conductivity and heat flux within the phase change material matrix. The results demonstrate that after reaching equilibrium within 20 ns, the total energy of the atomic sample converges to −5990.70 eV, indicating stable atomic oscillations. Notably, increasing Al₂O₃ nanoparticle concentration to 3 % significantly improves the heat flux and thermal conductivity, reaching values of 354.11 W/m2 and 405.42 W/m·K, respectively. The radial distribution function analysis shows a decrease in the maximum peak to 3.49 at the 3 % concentration, suggesting that a higher concentration of oxygen atoms in the material could enhance thermal performance. Furthermore, the maximum temperature within the system increases to 934.17 K at the 3 % atomic ratio. The aggregation time at this concentration is 8.11 ns, which decreases to 6.83 ns at a 10 % atomic ratio, further supporting the detrimental impact of nanoparticle aggregation. Notably, a 3 % concentration is found to be optimal for improving performance. These findings show the critical role of Al₂O₃ nanoparticles in enhancing the thermal performance of phase change material-based systems, offering valuable insights into optimal nanoparticle concentration and aggregation for effective thermal management in energy storage applications. © 2025 The AuthorsArticle Citation Count: 0Effect of Surface Coatings on Endothelialization and Biofilm in Ptfe Vascular Grafts(SAGE Publications Ltd, 2025) Erkan, M.H.; Boğa, M.; Salih, H.; Barbarus, E.; Rahman, Ö.F.; Sakarya, S.Polytetrafluoroethylene (PTFE) grafts are of great importance for vascular surgery and many methods have been developed to improve their biocompatibility. The most important of these methods is the coating of the inner surfaces of the grafts. In this study, the effects of surface coatings used in vascular grafts on endothelialization and bacterial biofilm formation were investigated. Three different PTFE graft types, heparin coated, carbon coated and uncoated, were compared. HUVEC cell culture was used for endothelialization experiments and Staphylococcus aureus strain was used for biofilm formation. Endothelialization was evaluated by inverted microscopy and scanning electron microscopy (SEM). Heparin-coated grafts showed more biofilm formation than other graft types (p < 0.01). Moderate biofilm formation was observed in carbon-coated grafts (p < 0.05). When evaluating endothelialization, heparin-coated grafts showed more cell adhesion in the first days, but lagged behind the other graft types in the following days. Carbon-coated grafts showed more endothelial cell proliferation in the long term. While biofilm formation was high in heparin-coated grafts, carbon-coated grafts provided better endothelialization. Our study showed that the coating of PTFE grafts significantly affects biocompatibility and infection risk. © The Author(s) 2025.Article Citation Count: 0Advancing Mechanical and Biological Characteristics of Polymer-Ceramic Nanocomposite Scaffolds for Sport Injuries and Bone Tissue Engineering: a Comprehensive Investigation Applying Finite Element Analysis and Artificial Neural Network(Elsevier Ltd, 2025) Lin, F.; Basem, A.; Khaddour, M.H.; Salahshour, S.; Li, W.; Sabetvand, R.In recent years, the application of polymer-ceramic nanocomposite scaffolds in bone tissue engineering has received considerable attention due to their structural similarity to natural bone tissue. Polycaprolactone (PCL) has emerged as a viable material for the fabrication of porous bone scaffolds. Composites that incorporate PCL with ceramic phases, such as nanocrystalline hydroxyapatite (n-HA) and tricalcium phosphate (TCP), have shown promise in promoting bone formation. Nevertheless, the use of bone scaffolds with complex geometries that mimic human bone poses challenges regarding their mechanical properties, which is the primary focus of this study. To assess the mechanical behavior of triangular nanostructures, particularly their ultimate compressive strength, finite element analysis (FEA) and artificial neural network (ANN) techniques were utilized. The obtained results were compared to experimental and analytical data. Three samples with varying weight percentages (0.1, 0.2, and 0.3) of HA and TCP nanoparticles embedded in PCL polymer were fabricated using a 3D fused deposition modeling technique. Scanning electron microscope (SEM) analysis was conducted to evaluate the morphology, while apatite formation rate and weight loss in simulated body fluid (SBF) and phosphate buffer saline (PBS) solution were assessed. The results revealed that a porosity of 76 % increases the apatite formation and dissolution rates by 23 % and 39 %, respectively. The SEM images, in conjunction with the simulated FEA models, indicated that scaffolds containing 0.3 wt% TCP nanoparticles exhibited favorable mechanical and biological properties for bone fracture applications. Additionally, the influence of different weight percentages of TCP and HA on the mechanical properties of the scaffolds was investigated using ANN. A neural network model was developed by incorporating 0.2 of each additive within a range of 0.1–0.3 while evaluating output data including elastic modulus, compressive strength, tensile strength, and Poisson's ratio. The predicted mechanical properties of the porous scaffold were subsequently analyzed and discussed. © 2025 Elsevier Ltd and Techna Group S.r.l.Article Citation Count: 0Using Different Evolutionary Algorithms and Artificial Neural Networks To Predict the Rheological Behavior of a New Nano-Lubricant Containing Multi-Walled Carbon Nanotube and Zinc Oxide Nano-Powders in Oil 10w40 Base Fluid(Elsevier B.V., 2025) Refaish, A.H.; Omar, I.; Hussein, M.A.; Baghoolizadeh, M.; Salahshour, S.; Emami, N.This study addresses the challenge of predicting and optimizing the viscosity of nano-lubricants containing Multi-walled Carbon Nanotubes and Zinc Oxide nanopowders suspended in 10W40 base oil. Accurate viscosity control is crucial for enhancing lubrication system performance. To achieve this, an artificial neural network based on the Group Method of Data Handling was developed, integrated with eight advanced evolutionary algorithms to improve prediction accuracy and optimize viscosity under varying conditions of solid volume fraction, temperature, and shear rate. The research bridges a significant gap by combining predictive modeling with multi-objective optimization, outperforming traditional artificial neural network methods. The use of advanced evolutionary algorithms enabled precise optimization of nano-lubricant properties, while the expanded parameter space provided deeper insights into the impact of operational conditions. The framework achieved a root mean square error of 13.569 and a correlation coefficient of 0.9965, highlighting its superior accuracy. Temperature was identified as the most influential factor, with a viscosity function margin of deviation of -0.88. Further optimization using a Genetic Algorithm determined optimal conditions of 1 % solid volume fraction, 55 °C temperature, and 875.577 s⁻¹ shear rate, resulting in an optimal viscosity of 32.722 cP. This study fills a critical gap in the literature, offering a novel framework for designing high-performance nano-lubricants and significantly advancing the field of lubrication science with improved prediction and optimization methodologies for industrial applications. © 2025 The Author(s)Article Citation Count: 0A Numerical Treatment Through Bayesian Regularization Neural Network for the Chickenpox Disease Model(Elsevier Ltd, 2025) Sabir, Z.; Mehmood, M.A.; Umar, M.; Salahshour, S.; Altun, Y.; Arbi, A.; Ali, M.R.Objectives: The current research investigations designates the numerical solutions of the chickenpox disease model by applying a proficient optimization framework based on the artificial neural network. The mathematical form of the chickenpox disease model is divided into different categories of individuals, susceptible, vaccinated, infected, exposed, recovered, and infected with/without complications. Method: The construction of neural network is performed by using the single hidden layer and the optimization of Bayesian regularization. A dataset is assembled using the explicit Runge-Kutta technique for reducing the mean square error using the training 76 %, while 12 %, 12 % for validation and testing. The whole stochastic procedure is based on logistic sigmoid fitness function, single hidden layer structure with thirty neurons, along with the optimization capability of Bayesian regularization. Finding: The designed procedure's correctness and reliability is observed by results matching, negligible absolute error around 10−04 to 10−06, regression, error histogram, and state transmission. Moreover, the best performance values based on the mean square error are performed as 10−09 to 10−11. Novelty: The current neural network framework using the construction of a single hidden layer and the optimization of Bayesian regularization is applied first time to solve the chickenpox disease model. © 2025 Elsevier LtdBook Part Citation Count: 1Development of an Acoustic Conduction Mechanism of a Metamaterial for Underwater Environment Applications(Springer Science and Business Media Deutschland GmbH, 2025) Sathish, K.; Ravikumar, C.V.; Imaduddin, M.; Yu-Chen, H.; Ahmadian, A.; Mehta, S.The reduction of engine noise is a challenging issue for devices that must operate silently. Noise is not only an annoyance, but it may also be utilized as a compass to identify clandestine vehicles, such as submarines. This is especially true when the stealthy vehicle in issue is involved. Traditional methods, such as identifying the source of the noise and taking the appropriate precautions to avoid it, could be used to regulate the noise level in a certain region. Due to the high mass density and low volume of the used materials, conventional construction techniques cannot be applied to underwater construction. It is crucial to develop innovative materials that have the potential to be employed in maritime applications. The study of acoustic metamaterials, which is currently a subject of significant attention because of its possible application in submarines, is frequently recognized as one of the most intriguing fields to have emerged in recent years. This chapter describes and highlights the benefits of acoustic metamaterials that have the potential to be utilized in submarines. Achieving high levels of sound absorption has been aided by the utilization of metamaterials, which are created by combining several materials of varying forms. The incorporation of numerous layers in the structure enhanced the material’s ability to absorb sound. Not only does the operation of the engine affect the level of background noise, but so do the characteristics of the numerous building components. Variations in engine speed and strain on the material cause a resonance effect, which is caused by the activation of the material’s intrinsic frequencies. Consequently, the use of sonar to pinpoint the precise location of submarines is fraught with danger. This study’s objective is to demonstrate the significance of the topic, as well as resonance protection measures and experimental results for resonance detection using acoustic analysis of metamaterial-based underwater acoustic channels. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Article Citation Count: 0Non-Local Piezoelasticity To Incorporate the Influence of Small-Scale Factors on the Resonance Behavior of the Mindlin Piezoelectric Polymeric Nanoplates(Elsevier Ltd, 2025) Sawaran Singh, N.S.; Hassan, W.H.; Ameen Ahmed, Z.M.; Al-zahy, Y.M.A.; Salahshour, S.; Pirmoradian, M.This study presents an investigation into the vibration resonance of Mindlin piezoelectric polymeric nanoplates under electromechanical loading, particularly in the presence of a rotating nanoparticle. The novelty of this research lies in the application of non-local piezoelasticity, which effectively incorporates the influence of small-scale factors on the resonance behavior of the nanoplate. By employing a variational approach to derive the governing equations, this work advances the understanding of how various parameters such as the non-local parameter, dimensions of the nanoplate, excitation voltage, and mass of the nanoparticle affect resonance frequencies. The Galerkin method is utilized to solve the partial differential equations governing the dynamics of the piezoelectric polymeric nanoplate, marking a significant methodological contribution to the field. The incremental harmonic balance approach is then applied to estimate the system's resonance frequencies, with numerical simulations confirming their existence. This research not only elucidates the complex interactions affecting resonance behavior but also highlights the potential for optimizing the design of nanostructures in various applications, including sensors and energy-harvesting devices. The findings suggest that increasing the non-local parameter softens the nanoplate's rigidity, leading to decreased resonance frequencies, while modifications in dimensions and applied voltages can enhance these frequencies. Overall, this study lays the groundwork for future explorations into the dynamic behavior of piezoelectric materials, emphasizing the importance of small-scale effects in nanotechnology applications. © 2025 The AuthorsArticle Citation Count: 0Optimizing the Thermostat Setting Points of Residential and Insulated Buildings in the Direction of Economic Efficiency and Thermal Comfort Through Advanced Multi-Purpose Techniques(Elsevier Ltd, 2025) He, P.; Ali, A.B.M.; Hussein, Z.A.; Singh, N.S.S.; Bains, P.S.; Saydaxmetova, S.; Alizadeh, A.The present research work develops a new approach for the optimization of thermostat setting and insulation designs in residential buildings located in various Iranian climates, including hot-humid, arid, temperate, and cool regions. The objective functions are set to minimize the construction cost, consumed electricity cost, and PPD to improve thermal comfort. Advanced computational techniques are integrated in a structured way to achieve the mentioned objectives. Numerical modeling is done through the simulation of building energy performance and thermal comfort using EnergyPlus. The exact mathematical relations between design variables and objective functions, which were heating setpoint and cooling setpoint, insulation thickness, and thermal conductivity, were identified using Multi-Polynomial Regression. MPR model has been validated respect to a wide set of statistical measures that included but were not limited to R², RMSE, and MAE for its high predictive accuracy. Then, multi-objective optimization is performed through NSGA-II, a well-known multi-objective optimization algorithm, which provides a Pareto front of optimal solutions balancing energy efficiency, cost, and comfort. Shannon's entropy method assigns weights to the Pareto-optimal solutions, whereas the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) selects the most suitable configurations for each city. Calculations show a great reduction in energy consumption to up to 82.66% at Bandar Abbas, with very important improvements in comfort, where the PPD is reduced between 31.1% to 56.3%. The predictive capacity of the MPR model was confirmed by this study, from the value of R², close to 1. The cost-effectiveness of the proposed solutions is underlined by minimizing construction and energy costs while preserving occupant comfort. This innovative approach adapts optimization strategies to regional climatic characteristics, providing practical solutions for sustainable and cost-effective building designs. The integration of advanced machine learning and genetic algorithms offers a scalable framework for future energy-efficient construction practices worldwide, contributing to reduced carbon footprints and enhanced occupant well-being. By addressing the limitations of previous studies and introducing a clear, structured methodology, this research provides valuable insights and practical tools for optimizing residential building performance in diverse climates. © 2025 Elsevier B.V.Article Citation Count: 0Investigating the Effect of Volume Fraction on Brownian Displacement, Thermophoresis, and Thermal Behavior of Graphene/Water Nanofluid by Molecular Dynamics Simulation(Elsevier Ltd, 2025) Lin, B.; Ali, A.B.M.; Babadoust, S.; Al-Zahy, Y.M.A.; Castañeda, J.L.Y.; Abdullaeva, B.; Esmaeili, S.Nanotechnology focuses on materials at the nanoscale, including nanoparticles and nanofluids are created by dispersing nanoparticles in a base fluid. This study examined the impact of volume fraction on thermophoresis, thermal conductivity, and Brownian motion in graphene/water nanofluid through molecular dynamics simulations. Simulations were performed at a constant temperature of 300 K, representative of room temperature conditions for thermal applications. This research aimed to understand how the amount of graphene in the water-based nanofluid affected these properties, which were crucial for heat transfer and thermal management systems. The study examined the effects of various nanoparticle volume fractions (1 %, 3 %, 6 %, and 10 %), ranging from dilute to semi-concentrated nanofluids, on thermal conductivity, Brownian motion, and thermophoresis. Results indicate an increase in average Brownian displacement and thermophoresis displacement from 3.06 and 23.88 Å to 4.14 and 26.88 Å, respectively, as the volume fraction increases from 1 % to 6 %. However, as the volume fraction increased from 6 % to 10 %, these values decreased to 3.35 Å and 23.99 Å. This decrease may be attributed to increased interparticle interactions and clustering at higher volume fractions. After 10 ns, increasing the nanoparticle volume fraction to 6 % raised heat flux and thermal conductivity from 39.54 W/m2 and 0.36 W/m·K to 45.05 W/m2 and 0.46 W/m·K. However, at a 10 % volume fraction, both parameters decreased to 39.56 W/m2 and 0.37 W/m·K, respectively. The temperature profile shows that increasing the graphene volume fraction to 6 % raised the maximum temperature from 1415 K to 1879 K; further increasing the volume fraction to 10 % decreased it to 1572 K. These findings indicate that the volume percentage of graphene nanoparticles significantly affected Brownian displacement, thermophoresis displacement, heat flux, thermal conductivity, and maximum temperature in the nanofluid. An optimal volume fraction of approximately 6 % is identified for enhancing thermal performance. Overall, the volume fraction, along with nanoparticle size, shape, and dispersion stability, was crucial in determining the atomic and thermal behavior of nanofluids, highlighting the need to identify the optimal concentration for superior performance. © 2024Article Citation Count: 0Accurate Prediction of the Rheological Behavior of Mwcnt-al2o3/Water-ethylene Glycol Nanofluid With Metaheuristic-Optimized Machine Learning Models(Elsevier Masson s.r.l., 2025) Ru, Y.; Ali, A.B.M.; Qader, K.H.; Abdulaali, H.K.; Jhala, R.; Ismailov, S.; Mokhtarian, A.The accurate prediction of the rheological properties of nanofluids is critical for optimizing their application in various industrial systems. This study focuses on the dynamic viscosity prediction of MWCNT-Al2O3/water (80 %) and ethylene glycol (20 %) hybrid nanofluid using machine learning approaches. A multilayer perceptron neural network (MLPNN) was employed for viscosity prediction, and its structural and training parameters, including the number of hidden layers and neurons, learning rate, training technique, and transfer functions, were optimized using three metaheuristic algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Marine Predators Algorithm (MPA). A dataset containing viscosity measurements influenced by nanoparticle volume fraction (VF), temperature (T), and shear rate (SR) was utilized. The optimization algorithms were evaluated over 10 and 20 runs for single-hidden-layer (1HL) and double-hidden-layer (2HL) MLPNNs, respectively. For the 1HL-MLPNN models, all three algorithms achieved nearly identical performance with high predictive accuracy (R = 0.99992, MSE = 0.00176). In contrast, for 2HL-MLPNN models, PSO outperformed MPA and GA with R = 0.99995 and MSE = 0.00105, followed by MPA (R = 0.99995, MSE = 0.00123) and GA (R = 0.99992, MSE = 0.00160). Also, sensitivity analysis revealed the VF as the most significant input parameter affecting viscosity predictions, followed by shear rate and temperature. These findings demonstrate the potential of metaheuristic-optimized MLPNNs for high-accuracy prediction of hybrid nanofluid rheological properties, facilitating improved design and application in thermal management systems. © 2025 Elsevier Masson SASNote Citation Count: 0Embryo Versus Endometrial Receptivity: Untangling a Complex Debate(Frontiers Media SA, 2025) Mercan, R.; Guzel, Y.; Usta, İ.; Alper, E.[No abstract available]Article Citation Count: 0Modeling the Effects of Pressure and Magnetic Field on the Phase Change of Sodium Sulfate/Magnesium Chloride Hexahydrate in Nanochannels(Elsevier B.V., 2025) Ali, A.B.M.; Hussein, R.A.; Singh, N.S.S.; Salahshour, S.; Pirmoradian, M.; Mohammad Sajadi, S.; Deriszadeh, A.This work examines the impact of different pressure levels (1 to 5 bar) and magnetic field frequencies (0.01 to 0.05 ps⁻¹) on the thermal behavior of sodium sulfate/magnesium chloride hexahydrate as a phase change material inside iron nanochannels, using molecular dynamics simulation. The system's kinetic and potential energies converge to 39.79 eV and -7204.99 eV, indicating the stability of the nanostructures. The impact of pressure and magnetic field frequency on heat flow, maximum temperature, and charge/discharge times was examined. Increasing the pressure from 1 to 5 bar reduced the heat flux and maximum temperature to 1509 W/m² and 391.18 K, respectively. Simultaneously, the charge duration extendes to 3.99 ns, whilst the discharge duration decreases to 4.30 ns. Moreover, increasing the magnetic field frequency from 0.01 to 0.05 ps⁻¹ results in a decrease in maximum temperature and heat flux, which fell to 415.67 K and 1566 W/m², respectively. The charge time decreases to 3.87 ns and the discharge time to 4.50 ns little owing to the increase in frequency. © 2025 The Author(s)Article Citation Count: 0Search for New Resonances Decaying To Pairs of Merged Diphotons in Proton-Proton Collisions at (formula Presented)(American Physical Society, 2025) Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J.W.; Bergauer, T.; Chatterjee, S.; Scodellaro, L.A search is presented for an extended Higgs sector with two new particles, (Formula presented) and (Formula presented), in the process (Formula presented). Novel neural networks classify events with diphotons that are merged and determine the diphoton masses. The search uses LHC proton-proton collision data at (Formula presented) collected with the CMS detector, corresponding to an integrated luminosity of (Formula presented). No evidence of such resonances is seen. Upper limits are set on the production cross section for (Formula presented) between 300 and 3000 GeV and (Formula presented) between 0.5% and 2.5%, representing the most sensitive search in this channel. © 2025 CERN, for the CMS Collaboration.Article Citation Count: 0The Effect of Copper Oxide Nanoparticles on the Thermal Behavior of Silica Aerogel/Paraffin as a Phase Change Material in a Cylindrical Channel With Molecular Dynamics Simulation(Elsevier Ltd, 2025) Yang, J.; Ali, A.B.M.; Al-zahy, Y.M.A.; Sawaran Singh, N.S.; Al-Bahrani, M.; Orlova, T.; Esmaeili, S.The thermal conductivity of phase change materials was substantially enhanced by nanoparticles, improving the overall performance of thermal energy storage systems through more efficient heat transfer during the phase change process. This study investigates the effect of varying amounts of copper oxide nanoparticles on the thermal behavior of silica aerogel/paraffin as a phase change material in a cylindrical channel. LAMMPS and molecular dynamics simulations were employed to analyze this using a computer program. Results show that the atomic sample density and velocity reached 0.1393 ų and 0.0119 Å/fs, respectively, with the addition of 5% nanoparticles to the target structure. The atomic samples also reached a maximum temperature of 635 K when 5% of nanoparticles were added. The heat flux and thermal conductivity increased from 66.43 W/m2 and 1.74 W/m·K to 71.25 W/m2 and 1.82 W/m·K with a CuO-NP concentration increase of 3%. Adding nanoparticles enhanced thermal conduction, improving the overall interaction between the PCM and the nanoparticles. This led to better thermal contact and reduced thermal resistance at interfaces. However, adding more nanoparticles may lead to agglomeration, where the nanoparticles cluster together instead of remaining evenly dispersed. This can negatively affect thermal properties, as agglomerated particles create larger voids in the material, reducing the effective contact area for heat transfer. Using molecular dynamics simulations provided valuable insights into optimizing nanoparticle concentration for improved thermal performance in energy storage applications. © 2025 Elsevier LtdArticle Citation Count: 0Ag and Al2o3/Water Two-Phase Transient Flow Analysis in a Double-Pipe Heat Exchanger Equipped With Baffles and Rotating Inner Tube(Elsevier Ltd, 2025) Al-Saad, M.; Ali, A.B.M.; Al-Mosallam, M.; Fares, M.N.; Fazilati, M.A.; Salahshour, S.; Sabetvand, R.Considering the wide application of double-pipe heat exchanger made their performance improvement very important. Employing aqueous nanofluid (NF) of Ag and Al2O3 as the working fluid inside the inner tube of the heat exchanger and its rotation as the respective passive and active enhancing methods are investigated numerically using the two-phase mixture method. The sensitivity analysis was performed to reveal the effect of Reynolds (Re) number, NF concentration and tube rotational speeds on heat transfer coefficient, heat transfer effectiveness, and efficiency ratio. The Re number, NF concentration, and rotation speed lie in 1000-3000, 0–4 %, and 300–500 rpm, respectively. The results show the higher improving effect of Ag rather than Al2O3 nanoparticle; for Re = 1000, 1500 and 2000 the efficiency ratio averaged between different concentrations are 39 %, 30 %, 20 % for Al2O3/water and 62 %, 65 % and 26 % for Ag/water NFs, respectively. By increasing the Re number, the enhancing effect of velocity increment on heat transfer rate prevails and hinders that of employing NF. Also, in rotating mode, the enhancement made by increasing the Re number is higher in the rotation speed of 500 rather than 300 rpm. The overall change of efficiency ratio versus the Re number increment is decreasing and the greatest improving effect of using NF is for the lowest Re numbers. Also, the enhancement due to increasing the Re number increment is higher at a rotational speed of 500 rather than 300 rpm. © 2025 The AuthorsArticle Citation Count: 0Thermal Behavior of Silica Aerogel-Paraffin Nanocomposites in a Nanochannel Under Varying Magnetic Fields: a Molecular Dynamics Study(Elsevier Ltd, 2025) Ru, Y.; Ali, A.B.M.; Babadoust, S.; Hussein, R.A.; Al-Bahrani, M.; Abdullaeva, B.; Esmaeili, S.The demand for efficient energy conservation methods is growing amid rising fuel costs and greenhouse gas emissions. Phase change materials are essential for thermal energy storage, and silica aerogels, when combined with these materials, are particularly effective for insulation. This study presented a novel analysis of how various magnetic field strengths (ranging from 0 to 0.5 T) affected the thermal behavior of a nanostructure composed of silica aerogel, paraffin, and CuO nanoparticles in a cylindrical tube. Using molecular dynamics simulations, we examined the magnetic field's effect on key thermal properties, including density, temperature, heat flux, thermal conductivity, and the charging and discharging times. Results indicate that increasing the magnetic field strength to 0.5 T led to a decrease in maximum density from 0.1385 to 0.1372 atoms/ų. Additionally, the maximum velocity increased to 0.0142 Å/fs, while the maximum temperature and heat flux rose to 646 K and 72.13 W/m2, respectively. The observed charging and discharging times were 5.91 ns and 8.52 ns, with stronger magnetic fields expediting the charging phase. These findings offer valuable insights into optimizing thermal energy storage systems through magnetic field modulation. © 2025 The AuthorsArticle Citation Count: 0Investigating the Effect of Electric Field Amplitude on the Thermal Behavior of Paraffin/Cu Nanostructure in a Tube Containing Non-Connected Rotating Ribs Using Molecular Dynamics Simulation(Elsevier Ltd, 2025) Sadeq, A.S.; Rasheed, R.H.; Albazzaz, S.; Fares, M.N.; Salahshour, S.; Sabetvand, R.This research investigates the impact of varying external electric field amplitudes on the atomic and thermal properties of a paraffin/copper composite in a tube with non-interconnected rotating ribs, using molecular dynamics simulation as the primary analytical tool. To ensure model accuracy, a preliminary equilibration phase is conducted for 10 ns under controlled conditions. This stabilized the temperature at 300 K and established a consistent total energy of 1.450 kcal/mol. After equilibration, an analysis examined how varying external electric field amplitudes influenced the thermal properties of composite with 7 % copper concentration. The results indicate that as external electric field amplitudes increased from 0.01 to 0.05 V/m, various parameters of the simulated atomic sample show notable variations. Specifically, maximum density decreased from 0.0848 to 0.0836 atom/ų, while maximum velocity increased from 0.00496 to 0.00519 atom/Å. Additionally, maximum temperature increases from 770 to 789 K, and heat flux increases from 5.59 to 5.71 W/m2. Thermal conductivity increases from 0.72 to 0.78 W/m·K, and charging time decreases from 6.17 to 5.99 ns. When external electric field amplitude increases from 0.01 to 0.03 V/m, discharge time decreases from 7.16 to 7.05 ns; however, at 0.05 V/m, discharge time slightly increases to 7.09 ns. These findings have practical implications for optimizing materials in thermal management and energy storage systems by tailoring electric field conditions to enhance performance. © 2025 The AuthorsArticle Citation Count: 0On Solution of Non-Linear Fde Under Tempered Ψ-Caputo Derivative for the First-Order and Three-Point Boundary Conditions(E.A. Buketov Karaganda University Publish house, 2024) Bensassa, K.; Benbachir, M.; Samei, M.E.; Salahshour, S.In this article, the existence and uniqueness of solutions for non-linear fractional differential equation with Tempered Ψ-Caputo derivative with three-point boundary conditions were studied. The existence and uniqueness of the solution were proved by applying the Banach contraction mapping principle and Schaefer's fixed point theorem. © 2024 The Authors.Article Citation Count: 0Anatomical and Morphometric Features of the Profunda Brachii Artery(Korean Association of Anatomists, 2024) Şanlıtürk, Y.N.; Zeybek, N.; Gayretli, Ö.; Öztürk, A.When the literature is examined, studies evaluating the profunda brachii artery (PBA) are limited as most studies only investigate the artery’s origin. In 44 upper extremities belonging to 24 human anatomical specimens, single and double PBAs were observed in 39 and five cases, respectively. In cases with a single PBA, the origin was the brachial artery (BA) in 35 cases and the posterior circumflex humeral artery in four cases. In cases with double PBAs, the artery’s origin was the BA. Morphometric measurements of single and double arteries originating from the first branch BA were evaluated separately and compared according to sex and side. Our study, in which the PBA was examined morphologically and morphometrically, contributes to the literature anatomically and radiologically in treating humerus fractures and lateral arm-flap applications by surgeons. Copyright © 2024. Anatomy & Cell Biology This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
