Abstract

This paper presents unsteady numerical results of double diffusive mixed convection flow in a trapezoidal enclosure with the uniform magnetic field effect applied in negative horizontal direction. At the bottom wall, the uniform and non-uniform heat and mass are applied while the heat and mass absorbed uniformly at the top wall. Other side walls are impermeable and adiabatic. The top wall moves along x-axis direction with a constant velocity. The transport phenomenon of this problem can be expressed by the coupled governing equation derived from the conservation of mass and momentum along with the energy equation for temperature and concentration. The finite element method (FEM) based on Galerkin weighted residual technique is used to compute the numerical result from these governing equations. The numerical computation is carried out for Lewis number (Le = 0.1–50) and Richardson’s number (Ri = 0.1–100). Computed numerical results of mass, temperature and velocity distribution are expressed graphically as iso-concentration lines, isotherm lines and streamlines respectively. Average Sherwood and Nusselt number values are used to show the mass and heat transfer rate from the heated and concentrated surface of the enclosure. It is found from the analysis that mass transfer strongly depends on Lewis number. Heat and mass transfer for uniformly heated and concentrated bottom wall is larger than the non-uniformly heated and concentrated bottom wall. Finally, a correlation has been done for average Nusselt and Sherwood numbers for both of the cases.

Abstract

This work is focussed on the numerical modeling of mixed convection heat transfer effects in a lid-driven cavity filled with a copper–water nanofluid. A heated wall mounted block with constant heat flux is attached along the vertical wall. The left vertical wall is maintained at higher temperature compared to the right vertical wall and the other (top and bottom) walls are insulated. A finite volume based numerical approach with QUICK scheme is used for the solution of nonlinear governing equations. A computational visualization technique is used to represent the two dimensional results of streamlines, isotherms, average Nusselt number and bulk-average temperature for a wide range of physical parameters, namely Reynolds number, Rayleigh number and solid volume fraction. The effective fluid flow and heat transfer variation are analyzed by placing the heated mounted block first along the left vertical wall (Case-I) and then along the right vertical wall (Case-II) to test the maximum heat transfer effects. The changes in main characteristics of the flow due to variation of Reynolds number and Rayleigh number are elaborated. The effect of various flow parameters on the thermal conductivity behavior for both cases is discussed based on average Nusselt number and bulk-average temperature and found that Case-I shows higher heat transfer rate compared to Case-II, for higher Re, Ra and ϕϕ.

Abstract

This paper investigates the influence of thermophoresis on mixed convection heat and mass transfer flow over a vertical wavy surface in a porous medium with variable properties, namely variable viscosity and variable thermal conductivity. The effect of wavy surface is incorporated into non-dimensional equations by using suitable transformations and then transformed into non-linear ordinary differential equations by employing the similarity transformations and then solved numerically. The transport process of flow, heat and mass transfer in the boundary layer for aiding and opposing flow cases is discussed. The structure of flow, temperature and concentration fields in the Darcy porous media are more pronounced by complex interactions among variable viscosity, variable thermal conductivity, mixed convective parameter, thermophoresis and amplitude of the wavy surface. Increasing thermophoresis parameter enhances velocity profile, concentration distribution and Sherwood number while reduces Nusselt number. As increase in variable viscosity, temperature and concentration distributions are enhanced while velocity profile, Nusselt number and Sherwood numbers are reduced. This study finds applications in aerosol Technology, space technology and processes involving high temperatures.

Abstract

In this work, we study the accuracy of CFD-based data-driven models, which predict comfortrelated flow parameters in a ventilated cavity with a heated floor. We compare the computational cost and accuracy of three different models, namely artificial neural network, support vector regression, and gradient boosting regression. The tested scenarios include short and long cavities with different inlet velocities. Among the studied frameworks, the artificial neural network provides the most accurate predictions for most of the tested flow configurations. However, test configurations with jet separation and a secondary vortex are more difficult to predict correctly; thus more high-fidelity data is required in order to construct a more robust and reliable model.