Faculty Publications

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Author: search.filters.author.Gnanasekaran, N.Subject: search.filters.subject.Heat transfer

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    Prediction of heat transfer with discrete heat sources in a vertical channel filled  ith high porosity metal foam
    (Dalian University of Technology, 2018) Kotresha, B.; Gnanasekaran, N.
    This paper discusses about the numerical prediction of isothermal condition with discrete heat sources in a vertical channel filled with high porosity metal foams. The problem considered consists of a vertical channel in which discrete heat source assembly is placed at the centre and high porosity metal foams are placed on either side of the aluminium plates to enhance the heat transfer. The flow through the metal foam porous medium is predicted by using Darcy Extended Forchheimer model and Local thermal non-equilibrium model as well as local thermal equilibrium model is used for heat transfer prediction. The results are presented in terms of temperature excess over the ambient for both empty and metal foam filled channel. Finally, the heat input through the discrete heat sources is varied to obtain an isothermal condition on all the heat sources at a constant inlet velocity. © 2018 by the authors of the abstracts.
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    Effect of sliding speed and rise in temperature at the contact interface on coefficient of friction during full sliding of SS304
    (Elsevier Ltd, 2019) Palanikumar, P.; Gnanasekaran, N.; Subrahmanya, K.; Kaliveeran, V.
    The present study focuses on the effect of sliding speed and rise in temperature on the coefficient of friction at the contact interface of SS304 alloys subjected to full sliding. Dry sliding experiments were conducted on Rotatory Type Pin on Disk Tribometer. Pins of 3 mm radius and 165 mm diameter circular disk having flat surface were fabricated to simulate Hertzian contact configuration. Experiments were conducted at three different sliding speeds of 1 m/s, 2 m/s and 3 m/s under constant normal load of 1 kg. All the experiments were conducted up to sliding distance of 100 m. From the full sliding experiments, the coefficient of friction decreased with increase in sliding speed and the stabilized coefficient of friction for SS304 alloy was in the range of 0.15-0.28. The temperatures due to friction were measured using K-type thermocouples and they were located to the pins at 4 mm and 7 mm distance from the contact surface. The temperature at the contact surface during dry sliding experiment was obtained from the acquired data using inverse heat transfer method. Temperature measured at different locations along the longitudinal axis of the pin increased with increase in sliding speed and sliding distance. The increase in temperature at the contact interface was observed due to increase in friction at the contact interface during sliding. The temperature had shown stabilized trend, when the coefficient of friction curve got stabilized during sliding process. © 2019 Elsevier Ltd.
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    Flow and Heat Transfer Phenomena Through Porous Media Under Turbulent Regime
    (Springer Science and Business Media Deutschland GmbH, 2024) Begum, S.D.; Trilok, G.; Gnanasekaran, N.
    Porous media are known to improve heat transfer and fluid flow properties at the expense of pressure drop. Numerical modelling techniques open up a broad scope of research avoiding colossal cost and time. The flow of fluid in an upright symmetrical passage is dealt through this numerical research. The numerical model consists of a heater plate assembly next to a partially filled porous metallic foam. Metal foams with 4 distinct PPIs of 10, 20, 30, and 45 and porosity spanning from 0.90 to 0.95 are the subject of numerical calculations. Various structural arrangements of the aforementioned porous media (combinations of various porosity and pore density) are considered. Heat is dispersed through forced convection with air as working fluid. This study's comparison focuses solely on the differences between laminar and turbulent flows when there is a porous media in terms of fluid flow characteristics and heat transfer qualities. The Darcy–Forchheimer equation, coupled with the local non-thermal equilibrium model, is incorporated in the partially filled metal foam region. Numerical outcomes of the laminar scenario are validated against the findings of earlier research. Reaffirming the solution process, the turbulent case's outcomes are compared. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    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.
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    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.
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    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.
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    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 University
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    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.
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    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.
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    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 Ltd