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Abstract Thermal energy storage systems based on Phase change materials (PCM) are an attractive option to bridge the temporal and spatial gap between the energy demand and supply. But, these systems possess poor thermal conductivity causing reduced rate of heat transfer. The objective of the present study is to numerically analyze the melting process in an optimized finned latent heat storage system dispersed with varying volume fraction of Graphene nano plates (GNP). The individual effect of incorporating fins, GNP and a combination of both at different volume fraction has been studied. Effective thermal conductivity of nano-composite PCM has been theoretically evaluated including the effect of aspect ratio, interfacial thermal resistance, anisotropy, non-linear effects as well as concentration for the dispersed GNP. In this work, Dynamic differential scanning calorimetry tests are performed to evaluate the phase change temperature, latent heat and specific heat of the sugar alcohol (d- mannitol). Transient variation of liquid fraction, average temperature and radial/longitudinal temperature differentials are presented which would be useful for designing medium temperature (160–200 °C) storage systems for various applications. Fin height is varied to obtain an optimum fin size such that natural convection currents are not impeded. Various heat transfer models (including natural convection) are analysed using the actual plant data of a double effect solar absorption system at different arrangements of fins and GNP. Effect of Reynolds number and inlet temperature of HTF on the system performance have also been studied. A reduction of 68% in total melting time is observed in finned LHSS with 5% GNP as compared to a conventional system.

Abstract Thermal energy storage systems based on Phase change materials (PCM) are an attractive option to bridge the temporal and spatial gap between the energy demand and supply. But, these systems possess poor thermal conductivity causing reduced rate of heat transfer. The objective of the present study is to numerically analyze the melting process in an optimized finned latent heat storage system dispersed with varying volume fraction of Graphene nano plates (GNP). The individual effect of incorporating fins, GNP and a combination of both at different volume fraction has been studied. Effective thermal conductivity of nano-composite PCM has been theoretically evaluated including the effect of aspect ratio, interfacial thermal resistance, anisotropy, non-linear effects as well as concentration for the dispersed GNP. In this work, Dynamic differential scanning calorimetry tests are performed to evaluate the phase change temperature, latent heat and specific heat of the sugar alcohol (d- mannitol). Transient variation of liquid fraction, average temperature and radial/longitudinal temperature differentials are presented which would be useful for designing medium temperature (160–200 °C) storage systems for various applications. Fin height is varied to obtain an optimum fin size such that natural convection currents are not impeded. Various heat transfer models (including natural convection) are analysed using the actual plant data of a double effect solar absorption system at different arrangements of fins and GNP. Effect of Reynolds number and inlet temperature of HTF on the system performance have also been studied. A reduction of 68% in total melting time is observed in finned LHSS with 5% GNP as compared to a conventional system.

Abstract Hybrid nanofluids are a novel class of colloidal fluids which have drawn significant attention due to potential tailoring of their thermo-physical properties for heat transfer enhancement by a combination of more than one nano-additive to meet specific requirements of an application. In the present work, ceramic copper oxide/carbon (SiO2-CuO/C) nanoparticles in 80:20 (wt%) composition were prepared by ultrasonic-assisted wet mixing technique. The hybrid nanofluid was formulated by dispersing the nanoparticles into a base fluid mixture of 60:40 (% by mass) glycerol and ethylene glycol (G/EG) using the two-steps method. The influence of nanoparticles on the augmentation of specific heat, thermal conductivity and viscosity was examined in the volume concentration range of 0.5–2.0% in the temperature range of 303.15–353.15 K. The results demonstrate that the synthesized SiO2-CuO/C hybrid nanoparticles enhanced the thermo-physical properties of the base fluid mixture which is higher than using SiO2 alone. In the case of SiO2–G/EG nanofluid, the specific heat capacity decremented by a maximum value of 5.7% whereas the thermal conductivity and viscosity incremented by 6.9% and 1.33-times as compared with G/EG at maximum volume concentration of 2.0% at a temperature of 353.15 K. Comparatively, a reinforcement of 80% SiO2 with 20% CuO/C in G/EG mixture led to thermal conductivity and viscosity enhancement by 26.9% and 1.15-times, respectively with a significant reduction of specific heat by 21.1%. New empirical correlations were proposed based on the experimental data for evaluation of thermophysical properties.

Abstract Hybrid nanofluids are a novel class of colloidal fluids which have drawn significant attention due to potential tailoring of their thermo-physical properties for heat transfer enhancement by a combination of more than one nano-additive to meet specific requirements of an application. In the present work, ceramic copper oxide/carbon (SiO2-CuO/C) nanoparticles in 80:20 (wt%) composition were prepared by ultrasonic-assisted wet mixing technique. The hybrid nanofluid was formulated by dispersing the nanoparticles into a base fluid mixture of 60:40 (% by mass) glycerol and ethylene glycol (G/EG) using the two-steps method. The influence of nanoparticles on the augmentation of specific heat, thermal conductivity and viscosity was examined in the volume concentration range of 0.5–2.0% in the temperature range of 303.15–353.15 K. The results demonstrate that the synthesized SiO2-CuO/C hybrid nanoparticles enhanced the thermo-physical properties of the base fluid mixture which is higher than using SiO2 alone. In the case of SiO2–G/EG nanofluid, the specific heat capacity decremented by a maximum value of 5.7% whereas the thermal conductivity and viscosity incremented by 6.9% and 1.33-times as compared with G/EG at maximum volume concentration of 2.0% at a temperature of 353.15 K. Comparatively, a reinforcement of 80% SiO2 with 20% CuO/C in G/EG mixture led to thermal conductivity and viscosity enhancement by 26.9% and 1.15-times, respectively with a significant reduction of specific heat by 21.1%. New empirical correlations were proposed based on the experimental data for evaluation of thermophysical properties.

ABSTRACTThe design of annular fin array with variable thickness fin profiles defined by B-spline curves is studied as a multi-objective optimization problem for simultaneously maximizing heat transfer rate and minimizing thermal stress. Maximization of surface efficiency and augmentation factor as well as minimization of fin volume are considered as additional objective functions for further assessment of fin array performance. Evaluating the objective values through hybrid spline difference method, different cases are investigated by solving the optimization model by non-dominated sorting genetic algorithm II. The proposed scheme should aid designers in selecting compromise optimal solutions for practical problems.

ABSTRACTThe design of annular fin array with variable thickness fin profiles defined by B-spline curves is studied as a multi-objective optimization problem for simultaneously maximizing heat transfer rate and minimizing thermal stress. Maximization of surface efficiency and augmentation factor as well as minimization of fin volume are considered as additional objective functions for further assessment of fin array performance. Evaluating the objective values through hybrid spline difference method, different cases are investigated by solving the optimization model by non-dominated sorting genetic algorithm II. The proposed scheme should aid designers in selecting compromise optimal solutions for practical problems.

Abstract It is well known that Espinosa-parades et al. (Espinosa-Paredes et al., 2011) proposed a fractional neutron point kinetic (FNPK) model with multi-group of delayed neutrons to describe dynamic behavior in a nuclear reactor. In (Aboanber and Nahla, 2016b), Aboanber and Nahla presented an extension of Espinosa-parades et al. FNPK model. This new model is called as the corrected fractional neutron point kinetic (CFNPK) model. The present study is concerned with the numerical solution of the CFNPK model (Aboanber and Nahla, 2016b) with six groups of delayed neutron precursors. The fractional derivative is described in the sense of Grunwald-Letnikov. An implicit finite difference method (FDM) is constructed for the solution of CFNPK model. The stability analysis of the method is carried out. We analyze the results of neutron density for different values of anomalous diffusion order, reactivity function, relaxation time and time step size. In addition, we compare the results corresponding to CFNPK model (Aboanber and Nahla, 2016b) with the results corresponding to the FNPK model proposed by Espinosa-parades et al. (Espinosa-Paredes et al., 2011). It is shown that as anomalous diffusion order decreases or simulation time increases the difference between the values of neutron density increases. We have investigated the effects of each term of the CFNPK.

Abstract It is well known that Espinosa-parades et al. (Espinosa-Paredes et al., 2011) proposed a fractional neutron point kinetic (FNPK) model with multi-group of delayed neutrons to describe dynamic behavior in a nuclear reactor. In (Aboanber and Nahla, 2016b), Aboanber and Nahla presented an extension of Espinosa-parades et al. FNPK model. This new model is called as the corrected fractional neutron point kinetic (CFNPK) model. The present study is concerned with the numerical solution of the CFNPK model (Aboanber and Nahla, 2016b) with six groups of delayed neutron precursors. The fractional derivative is described in the sense of Grunwald-Letnikov. An implicit finite difference method (FDM) is constructed for the solution of CFNPK model. The stability analysis of the method is carried out. We analyze the results of neutron density for different values of anomalous diffusion order, reactivity function, relaxation time and time step size. In addition, we compare the results corresponding to CFNPK model (Aboanber and Nahla, 2016b) with the results corresponding to the FNPK model proposed by Espinosa-parades et al. (Espinosa-Paredes et al., 2011). It is shown that as anomalous diffusion order decreases or simulation time increases the difference between the values of neutron density increases. We have investigated the effects of each term of the CFNPK.

AbstractWe demonstrate the high concentration exfoliation of graphene nanosheets in dimethyl formamide (DMF) as a solvent from graphite powder. UV-Vis-NIR spectroscopy shows low power bath sonication yields less concentration of graphene nanosheets exfoliation, whereas the high power probe sonication yields high concentration graphene nanosheets exfoliation. The concentration of graphene nanosheets exfoliation depends on amount of energy supplied, and there exists a linear relationship between the concentration of graphene and energy supplied during sonication. TEM micrograph confirms the exfoliation of graphene nanosheets. AFM studies shows; high power sonication for longer time reveals graphene exfoliation with fewer graphene layers. The strategy of bath sonication followed by probe sonication of grapheme solution shows the stable suspension of graphene nanosheets even after one month.