Search

The addition of nanoparticles into conventional heat transfer fluids is one of the modern science techniques that offer better heat transfer performance. However, micropolar fluid model is not considered under these nanoparticles effects. Therefore, the main objective of this study is to explore the nanofluids to understand the microstructure and inertial characteristics of nanoparticles. In this paper, heat transfer flow of a micropolar nanofluid mixture containing copper (Cu) and silver (Ag) nanoparticles is investigated over a heated horizontal circular cylinder. The dimensionless governing equations are solved via an implicit finite difference scheme known as Keller-box method. The results of the nanofluid mixture are compared with those with a Newtonian fluid. The effects of different parameters on velocity, angular velocity and temperature are examined graphically for both Cu/Ag-water and Cu/Ag-kerosene oil. Results show that the heat transfer coefficient of the Cu/Ag-kerosene oil nanofluid mixture is larger than that of the Cu/Ag-water nanofluid, when comparison is based on a fixed value of the micro-rotation parameter.

In this study, a mathematical model simulating the flow of ethylene glycol as a micropolar fluid supported by copper or graphene oxide nanoparticles around a cylinder affected by a magnetic field is established. A computational approximation is introduced for the solution of the governing mathematical model using the Keller-Box approximation. In addition, computations are executed with the aid of the MATLAB program to obtain numerical and graphical outcomes and validate and assess them. The graphical outcomes of the influential factors on the physical quantities related to energy transmission are analyzed and discussed. According to these outcomes, all physical groups are decreasing functions of the micropolar factor. With the exception of temperature, increasing the intensity of magnetic parameters has a negative impact on the studied physical groups. The fractional volume factor increases friction forces, the Nusselt number, and the temperature while decreasing velocity and angular velocity. [ABSTRACT FROM AUTHOR]

In recent years, many researchers have focused on forecasting financial time series data, especially stock market data. Stock market data possesses so many features that forecasting may be very challenging. In the present study, a hybrid of two methodologies is proposed, which is the Empirical Mode Decomposition (EMD) and the Random Walk (RW) to enhance the stock market forecasting performance, denoted by (EMD-RW). The advantage of EMD-RW is its ability to forecast nonlinear and nonstationary stock market data without the need to use some transformation method or differencing a time series technique. Moreover, the new proposed EMD-RW produced high-accuracy results. Ten stock market time series for ten different countries are used in this study to demonstrate the forecasting accuracy of the EMDRW. Results using four forecasting accuracy functions display that EMD-RW forecasting accuracy is better than the four compared methods. [ABSTRACT FROM AUTHOR]

A computational simulation of Williamson fluid flowing around a spherical shape in the case of natural convection is carried out. The Lorentz force and constant wall temperature are taken into consideration. In addition, upgrader heat transfer catalysts consisting of multi-walled carbon tubes, molybdenum disulfide, graphene oxide, and molybdenum disulfide are employed. The Keller box approach is used to solve the mathematical model governing the flow of hybrid Williamson fluid. To validate our findings, the key parameters in the constructed model are set to zero. Next, the extent of the agreement between our results and published results is observed. Numerical and graphical results that simulate the impressions of key parameters on physical quantities related to energy transmission are obtained, discussed, and analyzed. According to the results of this study, increasing the value of the Weissenberg number causes an increase in both the fluid temperature and drag force, while it also leads to a decrease in both the velocity of the fluid and the rate of energy transmission. Increasing the magnetic field intensity leads to a reduction in the rate of heat transfer, drag force, and fluid velocity while it has an appositive effect on temperature profiles. [ABSTRACT FROM AUTHOR]

In this study, a numerical investigation of free convection in magneto-hydrodynamic (MHD) Casson nanofluid flow with heat transfer over a stretching sheet and with constant heat flux boundary condition is done. A magnetic field is considered normal to the stretching sheet. Two types of nanoparticles with various conductivities, such as iron oxide and graphene oxide are suspended in ethylene glycol/water-based Casson nanofluid. An implicit finite difference scheme known as Keller-box method has been employed in order to solve the set of nonlinear partial differential equations resulted from the governing equations, namely continuity, momentum, and energy equations. The effects of the MHD Casson nanofluids parameters on the physical properties such that local skin friction coefficient, local Nusselt number, velocity, and temperature have been displayed and discussed. The study has revealed that ethylene glycol has higher velocity and less temperature than water with different values of nanoparticle volume fraction, magnetic, and Casson parameters with the existence of Fe3O4/GO nanoparticles. Comparisons with previous studies show that the proposed method is in good agreement with other results. [ABSTRACT FROM AUTHOR]

In this paper, the heat transfer flow of a micropolar nanofluid mixture containing three types of oxide nanoparticles namely titanium oxide (TiO2), alumina oxide (Al2O3) and graphene oxide (GO) which suspended in two different types of fluids such as water and kerosene oil are investigated over a heated horizontal circular cylinder with constant surface heat flux. The dimensionless form of governing equations are solved via an implicit finite difference scheme known as Keller-box method. The effects of nanoparticles volume fraction, Prandtl number, micro-rotation parameter on temperature, velocity and angular velocity are plotted and discussed. Further, numerical results for the local wall temperature and the local skin friction coefficient are obtained. It is found that the local wall temperature of Al2O3 based nanofluid is higher than the other oxide based nanofluid, but the local skin friction of GO is higher than the other oxide nanoparticles, for every values of nanoparticle volume fraction and micro-rotation parameter. The present results of local wall temperature and local skin friction for Newtonian fluid are found to be in good agreement with the literature. [ABSTRACT FROM AUTHOR]