Journal Articles
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884
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Item A neural network based method for estimation of heat generation from a teflon cylinder(Global Digital Central, 2016) Kumar, S.; Kumar, H.; Gnanasekaran, N.The paper reports the estimation of volumetric heat generation (qv) from a Teflon cylinder. An aluminum heater, which acts as a heat source, is placed at the center of the Teflon cylinder. The problem under consideration is modeled as a three dimensional steady state conjugate heat transfer from the Teflon cylinder. The model is created and simulations are performed using ANSYS FLUENT to obtain temperature data for the known heat generation qv. The numerical model developed using ANSYS acts as a forward model. The inverse model used in this work is Artificial Neural Network (ANN). Estimation of heat generation is carried out by minimizing the error between the simulated temperature and the experimental/surrogated temperature. The efficacy of the ANN method is explored for the estimation of unknown heat generation as both forward model and inverse model. The concept of Asymptotic Computational Fluid Dynamics (ACFD) is introduced as a fast forward model which is obtained by performing CFD simulations. The unknown heat generation is estimated for the surrogated data using ANN. In order to mimic experiments, noise is added to the surrogated data and estimation of heat generation is also carried out for the perturbed/noise added temperature data. © 2016, Global Digital Central. All rights reserved.Item A Markov Chain Monte Carlo-Metropolis Hastings Approach for the Simultaneous Estimation of Heat Generation and Heat Transfer Coefficient from a Teflon Cylinder(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2018) Kumar, H.; Kumar, S.; Gnanasekaran, N.; Balaji, C.This paper reports the use of Markov Chain Monte Carlo (MCMC) and Metropolis Hastings (MH) approach, to solve an inverse heat transfer problem. Three-dimensional, steady state, conjugate heat transfer from a Teflon cylinder of dimensions 100 mm diameter and 100 mm length with uniform volumetric internal heat generation is considered. The goal is to estimate volumetric heat generation and heat transfer coefficient, given the temperature data at certain fixed location on the surface of the cylinder. The internal volumetric heat generation is specified as input and the temperature and heat transfer coefficient values are obtained by a numerical solution to the governing equation. The temperature values also depend on heat transfer coefficient which is obtained by solving Navier–Stokes equation to obtain flow information. In order to reduce the computational cost, a neural network is trained from the computational fluid dynamics simulations. This is posed as an inverse problem wherein volumetric heat generation and heat transfer coefficient are unknown but the temperature data is known by conducting experiments. The novelty of the paper is the simultaneous determination of volumetric heat generation and heat transfer coefficient for the experimentally measured steady-state temperatures from a Teflon cylinder using MCMC-MH as an inverse model in a Bayesian framework and finally, the estimates are reported in terms of mean, maximum a posteriori, and the standard deviation which is the uncertainty associated with the estimated parameters. © 2018 Taylor & Francis Group, LLC.Item A Bayesian inference approach: estimation of heat flux from fin for perturbed temperature data(Springer India, 2018) Kumar, H.; Gnanasekaran, N.This paper reports the estimation of the unknown boundary heat flux from a fin using the Bayesian inference method. The setup consists of a rectangular mild steel fin of dimensions 250×150×6 mm3 and an aluminium base plate of dimensions 250×150×8 mm3. The fin is subjected to constant heat flux at the base and the fin setup is modelled using ANSYS14.5. The problem considered is a conjugate heat transfer from the fin, and the Navier–Stokes equation is solved to obtain the flow parameters. Grid independence study is carried out to fix the number of grids for the study considered. To reduce the computational cost, computational fluid dynamics (CFD) is replaced with artificial neural network (ANN) as the forward model. The Markov Chain Monte Carlo (MCMC) powered by Metropolis–Hastings sampling algorithm along with the Bayesian framework is used to explore the estimation space. The sensitivity analysis of the estimated temperature with respect to the unknown parameter is discussed to know the dependency of the temperature with the parameter. This paper signifies the effect of a prior model on the execution of the inverse algorithm at different noise levels. The unknown heat flux is estimated for the surrogated temperature and the estimates are reported as mean, Maximum a Posteriori (MAP) and standard deviation. The effect of a-priori information on the estimated parameter is also addressed. The standard deviation in the estimation process is referred to as the uncertainty associated with the estimated parameters. © 2018, Indian Academy of Sciences.Item A synergistic combination of Asymptotic Computational Fluid Dynamics and ANN for the estimation of unknown heat flux from fin heat transfer(Elsevier B.V., 2018) Kumar, H.; Gnanasekaran, N.This paper deals with conjugate heat transfer from a rectangular fin. The problem consists of mild steel (250 × 150 × 6 mm) fin placed vertically on aluminium base (250 × 150 × 4 mm). The aluminium plate is subjected to an unknown heat flux at the base. The fin set-up is modelled using ANSYS fluent 14.5. The fin geometry is surrounded by extended domain filled with air so as to account for natural convection conjugate heat transfer. Grid independence study is carried out to fix the number of grids. A simple correlation using Asymptotic Computational Fluid Dynamics (ACFD) is developed and the same is used as a forward model to obtain the temperature distribution considering heat flux as the input. The problem is treated as an inverse problem in which a non-iterative method, ANN is used as the inverse model to estimate the unknown heat flux from the information of temperature. The results of the forward model and the ANN predicted values are in close agreement with error less than 1%. Effect of noise on the unknown parameter is also studied extensively. © 2017 Faculty of Engineering, Alexandria UniversityItem Experimental Investigation on Heat Spreader Integrated Microchannel Using Graphene Oxide Nanofluid(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2020) Narendran, G.; Gnanasekaran, N.; Arumuga Perumal, D.A.Thermal design consideration is highly essential for efficient heat dissipation in advanced microprocessors which are subjected to conjugate heat transfer under high heat flux with a minimal area for cooling. Generally, these multicore processors develop a localized high density heat flux referred to as hotspot. The effective use of microchannel in order to mitigate the hotspot is found in literature; however, the flow induced hotspot still exist due to maldistribution of flow inside the microchannel. Henceforth, the present study provides an experimental insight on laminar forced convection in a parallel microchannel heat sink accompanied with 1.2 mm thin copper heat spreader with a surface area of 30 mm2 to effectively migrate the maldistribution flow induced hot spot. The present experimental study provides a profound insight about the hotspot and migration of hotspot to safe zones; as a result, not only the performance of the multi core microprocessor is highly improved but also the reliability of neighboring components is well secured. © 2019, © 2019 Taylor & Francis Group, LLC.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 Nuances of fluid flow through a vertical channel in the presence of metal foam/solid block – A hydrodynamic analysis using CFD(Elsevier Ltd, 2020) Kotresha, B.; Gnanasekaran, N.A numerical study is presented in this paper to examine the fluid flow in a vertical channel partly filled with porous metallic foams. The physical model comprises of aluminum plate-heater assembly placed in the vertical channel. Heat is carried away by the working fluid air from the plates inside the vertical channel through forced convection. High thermal conductivity metal foams are attached to the heater-plate assembly in order to reduce the temperature of the aluminum plates. Thus, the study pays attention only to the characteristics of fluid flow at different positions of the vertical channel in the presence of metal foams. The present analysis considers the Forchheimer – Extended Darcy equation for the metal foam to predict the fluid flow in conjunction with the local non-thermal equilibrium model for the analysis of heat transfer through the porous metal foams. At first, the methodology applied to the present numerical analysis is validated with the existing results. Upon reaffirming the solution methodology, the results of the metal foam study are then compared with a solid block that replaces the metal foam structure inside the vertical channel. Consequently, as a novel approach, the analysis enables one to arbitrate the tradeoff between the porous metal foam and the solid block for heat transfer augmentation from the plate assembly to the air. © 2020 Elsevier LtdItem Conjugate heat transfer study comprising the effect of thermal conductivity and irreversibility in a pipe filled with metallic foams(Springer Science and Business Media Deutschland GmbH, 2021) Jadhav, P.H.; Gnanasekaran, N.; Arumuga Perumal, D.A.A parametric study is proposed in this paper to examine heat dissipation rate and entropy generation of a forced convection in a horizontal pipe which is filled with high porous metallic foams. The study quantifies the effect of thermal conductivity and pore density on entropy generation when the pipe is fully filled with copper, aluminium and nickel metallic foams of 0.6 m length in the fluid flow direction. To predict fluid flow and heat transfer features through these metallic foams the Darcy-extended Forchheimer (DEF) flow and the local thermal non-equilibrium (LTNE) models are employed. The characteristics of laminar, transition and turbulent in the non-foam region of the pipe are captured by considering the appropriate flow models. To affirm the methodology adopted in this work, the results of the present numerical solutions are validated with the available experimental results reported in the literature. Colburn j factor and thermal performance factor are the important factors that decide the performance and efficiency of any heat exchange device. Hence, these parameters are critically evaluated and are observed to increase with increasing pore densities of the metal foams and decrease with increasing flow rates of the fluid. Furthermore, the numerical analysis is extended to obtain the results of wall temperature, Nusselt number, heat transfer enhancement ratio, frictional irreversibility and Bejan number. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.Item Performance evaluation of partially filled high porosity metal foam configurations in a pipe(Elsevier Ltd, 2021) Jadhav, P.H.; Gnanasekaran, N.; Arumuga Perumal, D.A.; Mobedi, M.In this contemporary research, a parametric analysis of partially filled high porosity metallic foams in a horizontal conduit is performed to augment heat transfer with reasonable pressure drop. The investigation includes six different models filled partly with aluminium foam by varying internal diameter of foams from the wall side and external diameter of foam from the core of the tube. The pore density of the foam ranges from 10 to 45 PPI and their porosity varies from 0.90 to 0.95. Flow dynamics are captured using Darcy Extended Forchheimer model for the porous filled region and two-equation turbulence k-? model employed in clear region of the fluid. The local thermal non-equilibrium assumption is incorporated in porous filled region of the conduit to compute the heat transport characteristics. The results showed that the thermal performance factor of 10 PPI aluminium foam performs close to the 10 PPI expensive copper foam. The performance factor is found to be higher for 30 PPI aluminium foam amongst the PPI's of the foam considered. However, the performance factor is found to be 2.93, 2.22 and 1.73 for 30PPI, 45 PPI and 20PPI with their porosities of 0.92, 0.90 and 0.90, respectively for the model 1, model 2 and model 3 at lower Reynolds number of 4500 and then it decreases progressively with increasing flow rates of the fluid. The results of average wall temperature, average Nusselt number and Colburn j factor are also evaluated to obtain best possible performance. © 2021Item Various trade-off scenarios in thermo-hydrodynamic performance of metal foams due to variations in their thickness and structural conditions(MDPI, 2021) Trilok, G.; Gnanasekaran, N.; Mobedi, M.The long standing issue of increased heat transfer, always accompanied by increased pressure drop using metal foams, is addressed in the present work. Heat transfer and pressure drop, both of various magnitudes, can be observed in respect to various flow and heat transfer influencing aspects of considered metal foams. In this regard, for the first time, orderly varying pore density (characterized by visible pores per inch, i.e., PPI) and porosity (characterized by ratio of void volume to total volume) along with varied thickness are considered to comprehensively analyze variation in the trade-off scenario between flow resistance minimization and heat transfer augmentation behavior of metal foams with the help of numerical simulations and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) which is a multi-criteria decision-making tool to address the considered multi-objective problem. A numerical domain of vertical channel is modelled with zone of metal foam porous media at the channel center by invoking LTNE and Darcy–Forchheimer models. Metal foams of four thickness ratios are considered (1, 0.75, 0.5 and 0.25), along with varied pore density (5, 10, 15, 20 and 25 PPI), each at various porosity conditions of 0.8, 0.85, 0.9 and 0.95 porosity. Numerically obtained pressure and temperature field data are critically analyzed for various trade-off scenarios exhibited under the abovementioned variable conditions. A type of metal foam based on its morphological (pore density and porosity) and configurational (thickness) aspects, which can participate in a desired trade-off scenario between flow resistance and heat transfer, is illustrated. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.