Abhishek Kumar Singh

Bio: Abhishek Kumar Singh is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Natural convection & Heat transfer. The author has an hindex of 7, co-authored 9 publications receiving 144 citations.

Visualization of Heat Transport during Natural Convection in a Tilted Square Cavity: Effect of Isothermal and Nonisothermal Heating

Abstract: Bejan's heatlines approach has been introduced to visualize heat flow during natural convection within a tilted square cavity inclined at an angle of ϕ = 30°. The enclosure is bounded by hot wall AB (case 1: isothermal heating and case 2: nonisothermal heating), isothermally cooled walls DA and BC in the presence of adiabatic wall CD. The results are presented in terms of streamlines, isotherms, heatlines, and local and average Nusselt numbers. The nonisothermal heating case produces the greater heat transfer rate at the center of the wall AB compared to that of the isothermal heating case, whereas the average Nusselt number shows an overall lower heat transfer rate for the nonisothermal heating case.

Role of entropy generation on thermal management during natural convection in tilted porous square cavities

Abstract: The strategic application of entropy generation concept for optimization of the natural convection process has been studied in the present work. The wall, AB is isothermally heated and walls, BC and DA are cooled in presence of adiabatic wall CD. The numerical results are presented in terms of isotherms (θ), streamlines (ψ) and entropy generation maps for heat transfer (Sθ) and fluid flow (Sψ) for various modified Prandtl numbers ( P r m = 0.015 and 1000), modified Darcy numbers ( D a m = 10 − 5 -- 10 − 2 ) and modified Rayleigh numbers ( R a m = 10 3 and 106). The maximum value of the entropy generation due to heat transfer (Sθ, max) is observed at hot and cold junction points (A and B), due to high temperature gradient, irrespective of Dam, Prm and inclination angles (φ). The active regions of Sθ occur at top portion of the walls, BC and DA at high Dam ( D a m = 10 − 2 ) and high Prm ( P r m = 1000). The maximum value of entropy generation due to fluid flow (Sψ, max) is found at various locations on the walls of the cavity whereas significant Sψ is also observed in the interior regions due to the friction between counter rotating circulation cells. The heat transfer rate along the wall AB ( N u ¯ AB ) and the total entropy generation (Stotal) are found to be constant for the conduction dominant regime ( 10 − 5 ≤ D a m ≤ 10 − 3 ) whereas non linear increasing trends are observed for convection dominant regime ( 10 − 3 ≤ D a m ≤ 10 − 2 ) . The inclination angle ranges, 30° ≤ φ ≤ 50° and 25° ≤ φ ≤ 75° are optimal tilt angles for P r m = 0.015 and 1000, respectively based on minimum entropy generation and reasonable heat transfer rate at high Dam ( D a m = 10 − 2 ) with R a m = 10 6 .

Introduction to the Finite Element Method

Abstract: This chapter introduces the finite element method (FEM) as a tool for solution of classical electromagnetic problems. Although we discuss the main points in the application of the finite element method to electromagnetic design, including formulation and implementation, those who seek deeper understanding of the finite element method should consult some of the works listed in the bibliography section.

Convection Heat Transfer

Abstract: Geometry: shape, size, aspect ratio and orientation Flow Type: forced, natural, laminar, turbulent, internal, external Boundary: isothermal (Tw = constant) or isoflux (q̇w = constant) Fluid Type: viscous oil, water, gases or liquid metals Properties: all properties determined at film temperature Tf = (Tw + T∞)/2 Note: ρ and ν ∝ 1/Patm ⇒ see Q12-40 density: ρ ((kg/m) specific heat: Cp (J/kg ·K) dynamic viscosity: μ, (N · s/m) kinematic viscosity: ν ≡ μ/ρ (m/s) thermal conductivity: k, (W/m ·K) thermal diffusivity: α, ≡ k/(ρ · Cp) (m/s) Prandtl number: Pr, ≡ ν/α (−−) volumetric compressibility: β, (1/K)

Nanofluid convective heat transfer using semi analytical and numerical approaches: A review

Abstract: The use of additives in the base fluid like water or ethylene glycol is one of the techniques applied to augment the heat transfer. Newly an innovative nanometer sized particles have been dispersed in the base fluid in heat transfer fluids. The fluids containing the solid nanometer size particle dispersion are called ‘nanofluids’. Two main categories were discussed in detail as the single-phase modeling which the combination of nanoparticle and base fluid is considered as a single-phase mixture with steady properties and the two-phase modeling in which the nanoparticle properties and behaviors are considered separately from the base fluid properties and behaviors. Both single phase and two phase models have been presented in this paper. This paper intends to provide a brief review of researches on nanofluid flow and heat transfer via semi analytical and numerical methods. It was also found that Nusselt number is an increasing function of nanoparticle volume fraction, Rayleigh number and Reynolds number, while it is a decreasing function of Hartmann number.