Browsing by Author "Şenol G."

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    A Review on Non-Newtonian Nanofluid Applications for Convection in Cavities under Magnetic Field
    (MDPI, 2023) Selimefendigil F.; Şenol G.; Öztop H.F.; Abu-Hamdeh N.H.
    This review is about non-Newtonian nanofluid applications for convection in cavities under a magnetic field. Convection in cavities is an important topic in thermal energy system, and diverse applications exist in processes such as drying, chemical processing, electronic cooling, air conditioning, removal of contaminates, power generation and many others. Some problems occur in symmetrical phenomena, while they can be applicable to applied mathematics, physics and thermal engineering systems. First, brief information about nanofluids and non-Newtonian fluids is given. Then, non-Newtonian nanofluids and aspects of rheology of non-Newtonian fluids are presented. The thermal conductivity/viscosity of nanofluids and hybrid nanofluids are discussed. Applications of non-Newtonian nanofluids with magnetohydrodynamic effects are given. Different applications of various vented cavities are discussed under combined effects of using nanofluid and magnetic field for Newtonian and non-Newtonian nanofluids. The gap in the present literature and future trends are discussed. The results summarized here will be beneficial for efficient design and thermal optimization of vented cavity systems used in diverse energy system applications. © 2022 by the authors.
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    A review on nanofluid, phase change material and machine learning applications for thermal management of hydrogen storage in metal hydrides
    (Elsevier Ltd, 2024) Şenol G.; Selimefendigil F.; Öztop H.F.
    This review is generally about some significant applications related to thermal management of hydrogen storage in metal hydrides. First, the importance of hydrogen energy is given. Second, an introductive piece of information about metal hydrides is given and the significance of metal hydride usage in hydrogen storage is discussed. In the next chapter, the concept of nanofluid usage in regard to thermal management of hydrogen storage in metal hydrides is given. Later, one of the thermal management techniques of hydrogen storage in metal hydrides, PCM (phase change material) usage, is discussed with studies related to the subjects in literature. Finally, different applications of machine learning in thermal management of hydrogen storage in metal hydrides are considered. It has been shown that thermal control for hydrogen storage in metal hydrides may be effectively achieved by employing nanofluids based on nanoparticles that have been carefully chosen for the system. Generally, Al2O3, CuO, MgO, Fe2O3, GO, GO-SiO2, and GO-TiO2 nanoparticles are used.in metal hydride storage thermal management system. The nanoparticle type and its loading amount are among the most important parameters that affect the improved performance of the hydrogen storage in metal hydrides. The quantity, melting temperature, thickness, thermal conductivity, depth of usage, and volume dispersion of PCMs are the fundamental parameters that are investigated in the studies for optimal values, taking into account additional parameters related to the metal hydride reactor systems, such as supply pressure, inlet velocity, temperature, etc. In order to get a faster response and a more compact hydrogen system, it is necessary to identify the ideal PCM thickness. Up to a certain degree, the hydrogen storage system benefits from PCM's higher thermal conductivity. The majority of machine learning research have been conducted to evaluate various characteristics and assess the potential of appropriate materials, metal hydrides, metals, material combinations, etc. for hydrogen storage. The findings of the studies under discussion have confirmed that machine learning is an effective, realistic means of predicting the parameters influencing hydrogen storage processes without sacrificing any of the drawbacks of experimental methods, such as high costs and lengthy search times. Future research should take into account more experimental investigations as well as a cost analysis of employing nanofluids and PCMs. © 2024 Hydrogen Energy Publications LLC