Faculty Publications

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    Inverse Estimation of Interfacial Heat Transfer Coefficient During the Solidification of Sn-5wt%Pb Alloy Using Evolutionary Algorithm
    (Pleiades journals, 2019) Vishweshwara, P.S.; Gnanasekaran, N.; Mahalingam, M.
    The study of the interfacial heat transfer coefficient (IHTC) is one of the major concerns during solidification of casting. In order to find out the IHTC at the metal–mold interface, a one dimensional transient heat conduction model is numerically investigated during horizontal directional solidification of Sn–5wt%Pb alloy. The forward model is solved using explicit finite difference method to obtain the exact temperatures for the known boundary conditions. The estimation of the unknown IHTC is attempted using Particle Swarm Optimization (PSO) as an inverse approach along with Bayesian framework. In order to prove the robustness of the proposed methodology, the estimation is accomplished for the simulated measurements. The simulated measurements are then added with noise to replicate the experimental data. The present approach not only minimizes the difference between simulated and measured temperatures but also takes in to account “a priori” information about the unknown parameters. © 2019, Springer Nature Singapore Pte Ltd.
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    Accelerating MCMC using model reduction for the estimation of boundary properties within Bayesian framework
    (Pleiades journals, 2019) Gnanasekaran, N.; Kumar, M.K.
    In this work, Artificial Neural Network (ANN) and Approximation Error Model (AEM) are proposed as model reduction methods for the simultaneous estimation of the convective heat transfer coefficient and the heat flux from a mild steel fin subject to natural convection heat transfer. The complete model comprises of a three-dimensional conjugate heat transfer from fin whereas the reduced model is simplified to a pure conduction model. On the other hand, the complete model is then replaced with ANN model that acts as a fast forward model. The modeling error that arises due to reduced model is statistically compensated using Approximation Error Model. The estimation of the unknown parameters is then accomplished using the Bayesian framework with Gaussian prior. The sampling space for both the parameters is successfully explored based on Markov chain Monte Carlo method. In addition, the convergence of the Markov chain is ensured using Metropolis–Hastings algorithm. Simulated measurements are used to demonstrate the proposed concept for proving the robustness; finally, the measured temperatures based on in-house experimental setup are then used in the inverse estimation of the heat flux and the heat transfer coefficient for the purpose of validation. © Springer Nature Singapore Pte Ltd. 2019.
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    Analysis of forced convection heat transfer through graded PPI metal foams
    (Pleiades journals, 2019) Kotresha, B.; Gnanasekaran, N.
    A forced convection heat transfer through high porosity graded Pores per inch (PPI) metal foam heat exchanger is numerically solved in this paper. The physical domain of the problem consists of a heat exchanger system attached to the bottom of a horizontal channel to absorb heat from the exhaust gas leaving the system. Two different pore densities of the metal foam 20 and 40 along with two different metal foam materials are considered for the enhancement of heat transfer in the present numerical investigation. The metal foam heat exchanger is considered as a homogeneous porous medium and is modeled using Darcy Extended Forchheirmer model. The heat transfer through the metal foam porous media is solved by using local thermal equilibrium (LTE) model. The effect of graded pore density and graded thermal conductivity is investigated and compared with the nongraded PPI metal foam. The heat exchanger system is simulated over a velocity range of 6–30 m/s. The pressure drop decreases for the graded pore density metal foams compared to the higher PPI metal foam and also increases with increase in the fluid inlet velocity. The results of temperature and velocity distribution for the graded and nongraded metal foams are compared and discussed elaborately. © Springer Nature Singapore Pte Ltd. 2019.
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    Parameter estimation using heat transfer models with experimental data using a combined ann-Bayesian approach
    (Begell House Inc., 2014) Gnanasekaran, N.; Shankar, N.T.; Balaji, C.
    A hybrid approach, wherein Markov Chain Monte Carlo simulations are used in a Bayesian framework, in conjunction with artificial neural networks (ANN) is developed for solving an inverse heat conduction problem. Steady state three-dimensional heat conduction from a Teflon cylinder with uniform volumetric internal heat generation is considered. The goal is to estimate qv, given the heat transfer coefficient h, the thermal conductivity k and temperature data at certain fixed locations on the surface of the cylinder. For the purposes of establishing the soundness and efficacy of the approach, temperatures obtained by a numerical solution to the governing equation for known values of the parameter qv are first used to retrieve the quantities of interest, followed by retrievals with actual measurements. In order to significantly reduce the computational time associated with the MCMC simulations, first, a neural network is trained with limited number of solutions to the forward model. This serves as a surrogate to replace the forward model (conduction equation) during the process of retrievals with Markov Chain Monte Carlo simulations in a Bayesian framework. The performance of the proposed hybrid technique is evaluated for different cases.
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    Conjugate Heat Transfer Studies in a Hexagonal Micro Channel
    (Elsevier Ltd, 2015) Hegde, S.; Narendran, N.; Gnanasekaran, N.
    This paper reports conjugate heat transfer studies in micro channel heat sink of 3 cm2 which acts as a sink for the heat generating material. The hexagonal micro channel is modeled with surface roughness to counter the manufacturing outcomes. Different combinations of Nano fluids such as ethylene glycol, isopropyl alcohol and de-ionized water are proposed in the numerical study and the maximum heat dissipation is obtained. Simulations are also carried out for various heat flux and different velocities of the fluids. The conjugate heat transfer model is helpful as a forward model in the field of inverse heat transfer wherein the unknown heat flux is estimated by either deterministic or stochastic models. © 2015 The Authors.
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    A New Forward Model Approach for a Mild Steel Fin under Natural Convection Heat Transfer
    (Elsevier Ltd, 2015) Kulkarni, A.S.; Kumar, H.; Gnanasekaran, N.
    This paper reports the correlation for temperature of the mild steel fin which is subjected to heat flux at its base. The study is performed on a two dimensional, steady state and laminar flow model. The numerical model is restricted to natural convection and the fluid under consideration is air. A rectangular mild steel fin (250 mm x 150 mm x 6 mm), aluminium base plate (250 mm x 150 mm x 8 mm) and an extended geometry representing the ambient air condition is modelled and simulated using ANSYS 14.5. Grid independence study is carried out to fix the number of grids in order to find the optimum number of nodes for carrying out simulations. The heat flux (q) at the bottom of the base plate is varied to study temperature distribution, surface heat transfer coefficient (h) and velocity profile of the flow in the boundary layer around the fin. All these parameters are studied by inclining the model at various angles. A multiple regression analysis is carried out to obtain correlation for the temperature in terms of angle of inclination and the heat flux. The main objective of the work is, proposing a model for the estimation of heat flux or heat transfer coefficient from the fin thereby reducing the computational cost of the forward model in the field of inverse heat transfer. © 2015 The Authors.
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    Synergestic approach for the simultaneous estimation of heat transfer coefficient and heat flux using fin from steady state heat transfer experiments
    (Begell House Inc., 2015) Kumar, H.; Kumar, S.; Srinivasa Sagar, K.; Gnanasekaran, N.
    This paper reports simultaneous estimation of heat transfer coefficient and heat flux from natural convection fin heat transfer. The experimental setup contains rectangular mild steel fin of dimensions (250×154×6 mm) and an aluminium base plate of dimensions (250×150×8 mm). A slot of 4mm depth is created at the center of aluminium plate along its length (250mm) and mild steel fin is press fitted into this slot. Eighteen calibrated K-type thermocouples are used to record the temperature of the base plate and the fin. Beneath the base plate, a heater is placed with the dimensions of the base plate. To restrict the heat loss, bottom and sides of the heater are insulated with glass wool. Steady state experiments are carried out for different heat input. The problem considered is an inverse problem where in heat transfer coefficient and heat flux can be estimated simultaneously for the given temperature data from experiments/surrogate data. The forward model uses Asymptotic Computational Fluid Dynamics (ACFD) to obtain temperature distribution for the assumed inputs (heat transfer coefficient and heat flux). A powerful Markov Chain Monte Carlo method along with Metropolis-Hastings algorithm is used to minimize the objective function. Finally, the estimated values of heat transfer coefficient and heat flux are reported in terms of mean. © 2021, Begell House Inc. All rights reserved.
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    Conjugate heat transfer in a Hexagonal micro channel using hybrid nano fluids
    (American Society of Mechanical Engineers, 2016) Hegde, S.S.; Narendran, N.; Gnanasekaran, N.
    Research is being focused on the use of micro channels with nano fluids as the heat sinks. This requires fundamental understanding of the heat transfer phenomenon in micro channels. The objective of this paper is to present results from a numerical study on laminar forced convection in a Hexagonal Micro Channel (HMC) heat sink. In particular, the numerical study is carried out using a single phase model. The fluid considered is Alumina-Copper hybrid Nano fluid. The performance of Al2O3+Cu+water is compared with Al2O3+water nano fluid and pure water with different volume fractions. The solid region of the channel is assumed as aluminum with a hydraulic diameter of 175μm. The solid and fluid regions of the micro channel are discretized using finite volume method by combining Navier Stokes equation and energy equation for conjugate heat transfer. The thermo physical properties for alumina nanoparticles are calculated by considering it as a spherical particle of 45nm diameter. The effect of surface roughness on convective heat transfer coefficient and pressure drop for the case of nano fluids is also considered. The analysis is further extended by adding pulsating input and by varying the velocity sinusoidally. The Brownian motion of nano particles is increased to study the efficiency of the heat sink. This ensures all the nano particles are in suspension and the randomness increases the micro convection in the fluid. Incorporating the pulsating flow increases the dispersion of the heat in the nano fluid at a faster rate and also decreases particle settlement in laminar flow. The combined effect of surface roughness and pulsating flow accounts for the change in the velocity profile and thermal boundary layer of the channel. Also the effect of surface roughness ranging from 0.2-0.6 is attempted and the variations in pressure drop, Nusselt number, and heat transfer coefficient are studied. The influence of hexagonal geometry and its interaction with alumina nano fluids is intensively studied by evaluating a three dimensional conjugate heat transfer model. The effect of side wall angle of 45°, 50° and 55° are computed to relate the velocity function with pressure drop, surface roughness and local heat transfer coefficient. The variation of Nusselt number with very low volume fraction of nano particles with a minimal amount of pressure drop is also presented. © 2016 ASME.
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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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    Asymptotic approach to obtain nusselt number correlation for laminar mixed convection in a vertical channel
    (Dalian University of Technology, 2018) Nakate, P.; Kotresha, B.; Gnanasekaran, N.
    In this paper, a general methodology is proposed for treating mixed convection problems in a vertical channel by the concept of asymptotic computational fluid dynamics (ACFD). Average Nusselt number is developed based on the limiting solutions of natural and forced convection.These correlations are then blended to find a unified composite correlation that work very well for extreme limits of mixed convection. For the purpose of demonstration, the problem of 2-D laminar, mixed convection in a vertical channel that comprises of a heater sandwiched between two aluminum plates has been used. Numerical simulations are performed with ANSYS-FLUENT to generate the required correlation. The study proposed in this work reveals that with minimum CFD solutions one can obtain a reasonably good composite correlation for the Nusselt number. © 2018 by the authors of the abstracts.