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    A new approach for enhancing the effectiveness of a regenerative heat exchanger by using organic and inorganic phase change material
    (Springer, 2024) Kılıç, Mustafa; Sahin, Mahir; Abdulvahitoglu, Asli
    The increasing need for energy, along with limiting resources, has encouraged the development of novel solutions in the fields of energy conservation and storage. Phase change materials (PCMs), which are differentiated by properties such as large energy storage capacities, chemical stability, and reactivity to reduced working temperatures, play an important role in addressing the need for energy conservation. The goal of this research is to identify the heat transfer properties of various organic and inorganic phase change materials, compare their performance under certain working situations, and assure their maximum efficiency. The study undertakes a numerical analysis of the heat transfer performance of diverse organic (RT31, RT50) and inorganic (SP31, SP50) phase change materials across varying Reynolds numbers (Re = 500, 1000, 1500, 2000) under laminar conditions within a regenerative double-pipe heat exchanger. The outcomes reveal that SP31 demonstrates a 16% higher heat transfer effectiveness than RT31, while SP50 surpasses RT50 by 18% in terms of heat transfer effectiveness. As the Reynolds number increases, so does the heat transfer effectiveness, total heat transfer coefficient, and number of transfer units (NTU) for all types of phase change materials, but the capacity ratio decreases. Notably, inorganic phase change materials exhibit superior heat transfer performance compared to their organic counterparts. The results obtained from this study have been evaluated to be potentially useful for enhancing energy efficiency and system performance in systems operating at low-temperature ranges by utilizing phase change materials in heat exchangers under specified flow conditions.Please check the edit made in the article title.
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    A thermohydrodynamic performance analysis of a fluid film bearing considering with geometrical parameters
    (Yildiz Technical Univ, 2023) Dal, Abdurrahim; Sahin, Mahir; Kılıç, Mustafa
    Bearing performance characteristics such as stiffness, and load capacity, are related to the lubrication fluid circulating through the gap. In the fluid film bearings, the characteristic of the lubrication film also depends on the journal geometry and the viscosity. This study aimed to research the bearing geometry influences on the thermohydrodynamic performance of a circular journal bearing. The temperature distribution is modeled using a 3-dimensional energy equation. The velocity components are obtained on the pressure distribution governed by Dowson's equation. Moreover, the heat transfer between the journal and oil is modeled with Fourier heat conduction equation, and the viscosity equation is derived for SAE10W30 commercial oil as a function of the temperature. An algorithm based on the finite difference method is developed, and a serial simulation is performed for different geometrical parameters such as bearing clearance, and bearing length-to-diameter ratio (L/D). When the radial clearance decreases from 150 i.tm to 100 i.tm, the maximum pressure grows up by 53%, and the maximum temperature decreases by 21%. On the other hand, when the L/D ratio rises from 0.8 to 1, the maximum pressure grows up by 22%, but the temperature distribution does not significantly change. The load capacity, and the stiffness are higher for low radial clearance. The load capacity, and the stiffness increase when the L/D ratio grows up.
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    Effects of geometrical parameters on thermohydrodynamic performance of a bearing operating with nanoparticle additive oil
    (Emerald Group Publishing Ltd, 2023) Dal, Abdurrahim; Sahin, Mahir; Kılıç, Mustafa
    PurposeBearing performance characteristics, such as stiffness and load capacity, are related to the viscosity of the fluid circulating through the gap. Nanoparticle additives in lubricant are one way to enhance of the viscosity. This study aims to investigate the effect of nanoparticle additives on the thermohydrodynamic performance of journal bearing with different bearing parameters. Design/methodology/approachThe temperature distribution is modeled using a three-dimensional energy equation. The velocity components are calculated on the pressure distribution governed by Dowson's equation. Moreover, the heat transfer between the journal and lubricant is modeled with Fourier heat conduction equation. On the other hand, the viscosity equation is derived for Al2O3 nanoparticles as a function of the volume ratio and the temperature. An algorithm based on the finite difference method is developed, and a serial simulation is performed for different parameters and different volume ratio of nanoparticle. FindingsWith the increase in the nanoparticle volume ratio, the maximum temperature decreases for the lower clearance values, but the addition of the nanoparticle influence on the maximum temperature reverses when the clearance grows up. The nanoparticle additives increase further the maximum temperature for higher values of L/D ratios. Moreover, the effects of the nanoparticle additives on the pressure are stronger at high eccentricity ratios for all bearing parameters. Originality/valueThis paper provides valuable design parameters for journal bearing with lubricant containing the nanoparticle additives.
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    Preservation of fruits through drying-A comprehensive review of experiments and modeling approaches
    (Wiley, 2024) Kılıç, Mustafa; Sahin, Mahir; Hassan, Aitazaz; Ullah, Atta
    A significant part of the world's population still has problems in accessing food. The growing world population will exacerbate this issue in the future. Innovative studies conducted in this field play a crucial role in addressing the issue of drying and storage of foods. Atmospheric drying methods, such as rotary, tunnel, conveyor, cabinet, tower, and kiln dryers, offer advantages in relation to high production capacities, cost-effective initial setup, and economical operating conditions. However, concurrently, the weaknesses of these methods arise from factors such as drying duration, uneven moisture content, and space requirements. The solar dryer method is especially effective in dehydrating agricultural products, offering an energy-saving advantage compared to other methods. However, it is important to note that this approach, which involves exposing crops to direct sunlight, comes with several drawbacks affecting both food quality and health. In cases where the quality of highly valued foodstuffs is crucial, subatmospheric drying methods like vacuum, freeze, and microwave freeze are typically preferred. However, the primary drawback of this approach lies in its high operating costs, particularly in terms of energy consumption. Artificial neural networks (ANNs) can be used for predictive modeling, helping to forecast drying behavior and optimize process parameters in food drying applications especially nonlinear connections among variables. ANNs are adept at managing nonlinearities, offering a more precise depiction of the intricate interactions within food drying systems. This review examines articles from the last 5 years in the literature, synthesizing research conducted in food drying. The findings indicate a predominant interest among researchers in methodologies with lower environmental impact, prompting increased attention to studies addressing this aspect. There is a notable emphasis on the frequent exploration of energy-efficient systems. The ongoing research focuses on the development of methods utilizing ultrasonic, infrared radiation, and electrohydrodynamic techniques to achieve more effective, shorter-duration, energy-efficient drying processes with enhanced control over the final product. This study addresses global food access challenges, highlighting the impact of population growth. It explores atmospheric and subatmospheric drying methods, emphasizing the effectiveness of solar drying for energy savings. The review delves into artificial neural networks for predictive modeling in food drying, revealing a growing interest in environmentally friendly and energy-efficient drying techniques, including ultrasonic, infrared radiation, and electrohydrodynamic methods for improved control and shorter durations. image
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    Reliable prediction of thermophysical properties of nanofluids for enhanced heat transfer in process industry: a perspective on bridging the gap between experiments, CFD and machine learning
    (Springer, 2023) Ullah, Atta; Kılıç, Mustafa; Habib, Ghulam; Sahin, Mahir; Khalid, Rehan Zubair; Sanaullah, Khairuddin
    In recent years, traditional fluids are frequently being replaced by efficient heat transfer fluids showing physical and thermal stability. One such category of fluids is called nanofluids, in which solid nanoparticles (metals or their oxides, nitrides and so on) are suspended in a base fluid resulting in enhanced heat transfer characteristics. These nanofluids are increasingly used in low to medium temperature applications toward intensification of process and power plants by reducing the overall size and heat losses. However, as compared to a pure fluid, prediction of thermal and physical properties of nanofluids is a challenge due to unavailability of a general model. These thermal and hydraulic characteristics are strongly dependent upon multiple factor including particle size, particle volume concentration, particle composition, particle shape, temperature, base fluid material, pH and shear rate. Keeping these challenges in mind and availability of modeling tools, we first summarize and comment on popular correlations available to predict thermal and physical properties of nanofluids. Then, a general approach for carrying out reliable computational fluid dynamics (CFD) simulations is presented. The limitation of a general correlation of physical properties for input into CFD code can be overcome by use of machine learning (ML) tools such as artificial neural networks (ANN) taking advantage of the huge databank of physical properties of nanofluids. The use of ML to compliment CFD for accurate and reliable simulation of systems employing nanofluids as working fluids is highlighted at the end as potential emerging areas of research. [GRAPHICS] .