Hartmann number

About: Hartmann number is a research topic. Over the lifetime, 2593 publications have been published within this topic receiving 61342 citations.

Entropy generation analysis of magnetohydrodynamic induction devices

Abstract: Magnetohydrodynamic (MHD) induction devices such as electromagnetic pumps or electric generators are analysed within the approach of entropy generation. The flow of an electrically-conducting incompressible fluid in an MHD induction machine is described through the well known Hartmann model. Irreversibilities in the system due to ohmic dissipation, flow friction and heat flow are included in the entropy-generation rate. This quantity is used to define an overall efficiency for the induction machine that considers the total loss caused by process irreversibility. For an MHD generator working at maximum power output with walls at constant temperature, an optimum magnetic field strength (i.e. Hartmann number) is found based on the maximum overall efficiency.

Boundary element method solution of MHD flow in a rectangular duct

Abstract: SUMMARY The magnetohydrodynamic (MHD) flow of an incompressible, viscous, electrically conducting fluid in a rectangular duct with an external magnetic field applied transverse to the flow has been investigated. The walls parallel to the applied magnetic field are conducting while the other two walls which are perpendicular to the field are insulators. The boundary element method (BEM) with constant elements has been used to cast the problem into the form of an integral equation over the boundary and to obtain a system of algebraic equations for the boundary unknown values only. The solution of this integral equation presents no problem as encountered in the solution of the singular integral equations for interior methods. Computations have been carried out for several values of the Hartmann number (1 < M < 10). It is found that as M increases, boundary layers are formed close to the insulated boundaries for both the velocity and the induced magnetic field and in the central part their behaviours are uniform. Selected graphs are given showing the behaviours of the velocity and the induced magnetic field.

Prediction of MHD flow and entropy generation by Artificial Neural Network in square cavity with heater-sink for nanomaterial

Abstract: Numerical analysis of magneto-hydrodynamic flow has been a matter of concern for research engineers and scientists. In this paper, magneto-hydrodynamic convection in square tank occupied with Cu-H 2 O nanomaterial is investigated for different configurations of heater-sink, in which Artificial Neural Network (ANN) model was used as an advanced predictive tool. The active semi-circular thermal location (heater and sink) at the left- right vertical sides are kept constantly at high and low temperatures respectively, whereas other walls are kept adiabatic. To reach the solution, Galerkin residual finite element analysis has been implemented. The investigation has been done for Hartmann number (Ha = 0 – 100), Rayleigh number (Ra = 103-107) and nanomaterial concentration ( φ = 0 – 0.05) and finally, streamlines, isotherm contours and entropy generation contours are discussed thoroughly. The overall heat transfer and generation entropy are quantitatively investigated by overall Nusselt number (Nu) and Bejan number (Be), respectively. Existence of external Lorentz forces affects on both non-dimensional performance parameters, Nu and Be. Finally, the higher heat transfer is found for middle–middle configuration of heater-sink walls. The impact of Ha and φ on Nu and Be found from the numerical heat transfer analysis has been predicted and compared with ANN prediction model. To be noted, ANN is widely used technique to compare and predict different experimental and numerical data accurately in many engineering applications.