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Modeling, Simulation, and Analysis of Electric Motors
Published in Wei Tong, Mechanical Design and Manufacturing of Electric Motors, 2022
A comprehensive review has been made by Boglietti et al. [14.34] on the evolution and modern approaches in the thermal analysis of electrical machines. The three primary thermal analysis methods, that is, lumped-parameter thermal network (LPTN), FEA, and CFD, are analyzed in depth and compared in order to highlight the qualities and defects of each. The thermal network is the most basic form to calculate conduction, convection, and radiation resistances for different parts of the motor construction. The convection heat transfer coefficient is most often based on empirical convection correlations. This is fundamentally different from CFD analysis, where the heat transfer coefficient is calculated from the CFD model itself. According to Boglietti et al., FEA can only be used to model conduction heat transfer in solid components. They expect that CFD will be more popular and widespread in the thermal analysis due to the fast development in computational capability of modern computers, as well as the cost reduction of CFD software.
Heat Transfer
Published in Albert Thumann, Scott Dunning, Plant Engineers and Managers Guide to Energy Conservation, 2020
Convection is the transfer of heat between a fluid, gas, or liquid. Equation (6-2) is indicative of the basic form of convective heat transfer. U, in this case, represents the convection film conductance, Btu/ft2 ⋅ hr ⋅ °F.
Waste Heat Recovery
Published in Albert Thumann, D. Paul Mehta, Handbook of Energy Engineering, 2020
Convection is the transfer of heat to or from a fluid, gas, or liquid. Formula 5-4 is indicative of the basic form of convective heat transfer. U0, in this case, represents the convection film conductance, Btu/ft2 • hr • °F.
Effect of thermal radiation and nth order chemical reaction on non-Darcian mixed convective MHD nanofluid flow with non-uniform heat source/sink
Published in International Journal of Ambient Energy, 2023
Arindam Sarkar, Hiranmoy Mondal, Raj Nandkeolyar
Convection is an important property during the investigation of fluid flow. Convection is of two types, natural convection and forced convection. Natural convection happens due to gravity, whereas forced convection causes by external forces. Convection is significant in the manufacturing of many electronic devices, heat exchangers, solar cells and so many engineering implementations. Chamkha and Khaled (2000) investigated the hydromagnetic mixed convective nanofluid flow passing a porous media. Sadr et al. (2022) studied the mixed convective nanofluid flow contained in a rotating heated cylinder. Bafakeeh et al. (2022) scrutinised both the free and forced convective nanofluid flow considering the slip velocity. They conclude that enhancement of the thermal profile is growing for the suspension of silver nanosised particles in kerosine oil. 2D mixed convective thermal property analysed by Abderrahmane et al. (2022). In addition, the inspection of the Peclet number and Reynolds number over 2-dimensional micropolar fluid passing through a horizontal channel has been investigated by Shamshuddin et al. (2023). Mandal et al. (2023) examined the effect of mixed convection on hybrid nanofluid flow. On the other hand, the analysis of entropy generation through mixed convective nanofluid flow was scrutinised by Raja et al. (2022).
Fully decoupled, linear and unconditional stability implicit/explicit scheme for the natural convection problem
Published in Applicable Analysis, 2023
The natural convection problem is an important system with the dissipative nonlinear terms in fluid dynamics; it describes incompressible flow driven by heat difference (refer to [1–4] and the references therein). The natural convection phenomena are ubiquitous in real life, such as indoor and outdoor ventilation, ocean and atmospheric flow, cooling of thermal and hydraulic equipment, etc. From the viewpoint of mathematical modeling, the natural convection problem is composed of the incompressible Navier–Stokes equations and the convection–diffusion equation, and fluid and temperature are coupled by the buoyancy and convection terms. More precisely, it is given as follows in dimensionless form where be a bounded domain assumed to have Lipschitz continuous boundary and to satisfy a further condition stated in (A1) –(A2). The letters u, p, T are the fluid velocity, pressure and temperature, respectively. is the final time, f and g are the body forces, is a unit vector in the direction of gravitational acceleration, Pr, Ra and κ refer to the Prandtl, Rayleigh numbers and the thermal conductivity parameter, respectively.
Numerical Investigation of Natural Convection and Irreversibilities between Two Inclined Concentric Cylinders in Presence of Uniform Magnetic Field and Radiation
Published in Heat Transfer Engineering, 2022
Ahmad Hajatzadeh Pordanjani, Saeed Aghakhani
Free convection is extensively used as a heat transfer mechanism, especially in simple and everyday devices, since there is no energy requirement for generating such heat transfers. Ovens, furnaces, and even the air heated in homes by a heat source are simple examples of natural convection heat transfer. There has been a great interest in this heat transfer mechanism for many years [1–5]. Natural convection occurs due to a temperature gradient in enclosures. Enclosures with a simple geometry allow for the evaluation of thermal and fluid phenomena. Accordingly, the effects of nanofluids (NFs), radiation, porous media and many other factors on natural convection inside such configurations have been investigated in the literature [6–11]. According to the literature, NFs have been extensively used in enclosures and have recently received much attention due to higher thermal conductivity than conventional fluids [12–18]. Researchers Das et al. [19], Putra et al. [20], Chon et al. [21] have shown that adding Al2O3 nanopowder (NP) to the base fluid (water) increases the parameter thermal conductivity (φ = 4%) by 9.4, 24 and 29 percent. Ghasemi and Aminossadati [22] used the SIMPLE algorithm to simulate natural convection in a water-filled rectangular enclosure containing CuO NP. Raising the Rayleigh (Ra) number leads to a rise in the Nusselt (Nu) number, and that using the water–CuO NF instead of the simple fluid enhanced the heat transfer rate.