Faculty Publications
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Item Natural Convection Through High Porosity Metal Foams—A Numerical Study(Springer Science and Business Media Deutschland GmbH, 2021) Kotresha, B.; Jadhav, P.H.; Gnanasekaran, N.Numerical analysis of natural convection through highly porous metal foams attached to the aluminium plates is performed in this study. A heater sandwiched between two aluminium plates attached with aluminium metal foams of different pores per inch (PPI) is considered for the present analysis. Initially, experiments are carried out for aluminium plate-heater assembly for different heat inputs. In the numerical investigation, the aluminium plates are attached with metal foams on either side for further analysis. A well-known Darcy extended Forchheimer flow and LTNE thermal models are considered for the metal foam in the computations. The natural convection is modelled using Boussinesq approximation. Initially, the numerical result for the plate without metal foam is validated with the experimental results for different heat inputs. The results show that the Nusselt number decreases with the increase of metal foam pore density (PPI) and increases with the increase in Rayleigh number. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item A combined ANN-GA and experimental based technique for the estimation of the unknown heat flux for a conjugate heat transfer problem(Springer Verlag service@springer.de, 2018) Kumar, M.K.; Vishweshwara, P.S.; Gnanasekaran, N.; Balaji, C.The major objectives in the design of thermal systems are obtaining the information about thermophysical, transport and boundary properties. The main purpose of this paper is to estimate the unknown heat flux at the surface of a solid body. A constant area mild steel fin is considered and the base is subjected to constant heat flux. During heating, natural convection heat transfer occurs from the fin to ambient. The direct solution, which is the forward problem, is developed as a conjugate heat transfer problem from the fin and the steady state temperature distribution is recorded for any assumed heat flux. In order to model the natural convection heat transfer from the fin, an extended domain is created near the fin geometry and air is specified as a fluid medium and Navier Stokes equation is solved by incorporating the Boussinesq approximation. The computational time involved in executing the forward model is then reduced by developing a neural network (NN) between heat flux values and temperatures based on back propagation algorithm. The conjugate heat transfer NN model is now coupled with Genetic algorithm (GA) for the solution of the inverse problem. Initially, GA is applied to the pure surrogate data, the results are then used as input to the Levenberg- Marquardt method and such hybridization is proven to result in accurate estimation of the unknown heat flux. The hybrid method is then applied for the experimental temperature to estimate the unknown heat flux. A satisfactory agreement between the estimated and actual heat flux is achieved by incorporating the hybrid method. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.Item Evaluation of artificial neural network in data reduction for a natural convection conjugate heat transfer problem in an inverse approach: experiments combined with CFD solutions(Springer, 2020) Kumar, M.K.H.; Vishweshwara, P.S.; Gnanasekaran, N.In this work, natural convection fin experiments are performed with mild steel as the fin and an aluminium plate as base. The dimension of the mild steel fin is 250 mm × 150 mm × 6 mm and the aluminium base plate is 250 mm × 150 mm × 8 mm. A heater is provided on one side of the aluminium base plate and the mild steel fin emerges on the other side of the plate. The heater provides required heat flux to the fin base; several steady-state natural convection experiments are performed for different heat fluxes and corresponding temperature distributions are recorded using thermocouples at different locations of the fin. In addition, a numerical model is developed that contains the dimensions of the fin set-up along with extended domain to capture the information of the fluid. Air is treated as a working fluid that enters the extended domain and absorbs heat from the heated fin. The temperature and the velocity of the fluid in the extended domain are obtained by solving the Navier–Stokes equation. The numerical model is now treated as a forward model that provides the temperature distribution of the fin for a given heat flux. An inverse problem is proposed to determine the heat flux that leads to the temperature distributions during experiments. The temperature distributions of the experiments and forward model are compared to identify the unknown heat flux. In order to reduce computational cost of the inverse problem the forward model is then replaced with artificial neural network (ANN) as data reduction, which is developed using several computational fluid dynamics solutions, and the inverse estimation is accomplished. The results indicate that a quick solution can be obtained using ANN with a limited number of experiments. © 2020, Indian Academy of Sciences.Item Numerical assessment of thermal characteristics of metal foams of orderly varied pore density and porosity under different convection regimes(Elsevier Masson s.r.l., 2022) Trilok, G.; Kumar, K.K.; Gnanasekaran, N.; Mobedi, M.The present study is done to analyze heat transfer and fluid flow in a channel with orderly varied pore density and porosity combination of foam samples. Darcy Forchheimer flow and LTNE thermal models are considered to estimate heat transfer characteristics. Considering the effect of orderly varied combinations of the dual structural properties, forced convection over a range of flow velocities and natural convection phenomenon are studied numerically in the channel housing porous samples. Two limiting solutions for Nusselt number (Nu) i.e., Nun (for natural convection) and Nuf (for forced convection) for Ri→∞ and Ri→0 respectively, as a function of independent variable Richardson number (Ri) with structural properties pore density and porosity are obtained with the help of local thermal non-equilibrium (LTNE) thermal model and Darcy-Forchheimer flow model. Further these asymptotic solutions are blended using technique illustrated in the literature in order to obtain solution for Nusselt number for mixed convection (Num). Correlations for Nusselt number as a function of combination of porosity and pore density are obtained emphasizing on the varied significance of these parameters in different convection regime. The present study not only emphasizes on effect of combination of structural properties of metal foams on heat transfer characteristics, but also illustrates a technique that enables to arrive at suitable correlation for an intermediate phenomenon existing between two other extremes, with zero computational cost. Effect of pore density on heat transfer characteristics at a given porosity, is found to be not much influencing in natural convection dominant regime. However, in mixed and forced convection dominant scenario it is illustrated that, effect of variation in pore density and porosity plays a significant role in expressing distinguishable heat transfer characteristics, along with other well-known independent parameters such as porosity and Reynolds number. © 2021 Elsevier Masson SAS