Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
13 results
Search Results
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 Investigation of Mixed Convection Heat Transfer Through Metal Foams Partially Filled in a Vertical Channel by Using Computational Fluid Dynamics(American Society of Mechanical Engineers (ASME) infocentral@asme.org, 2018) Kotresha, B.; Gnanasekaran, N.Two-dimensional computational fluid dynamics simulations of mixed convection heat transfer through aluminum metal foams partially filled in a vertical channel are carried out numerically. The objective of the present study is to quantify the effect of metal foam thickness on the fluid flow characteristics and the thermal performance in a partially filled vertical channel with metal foams for a fluid velocity range of 0.05-3 m/s. The numerical computations are performed for metal foam filled with 40%, 70%, and 100% by volume in the vertical channel for four different pores per inch (PPIs) of 10, 20, 30, and 45 with porosity values varying from 0.90 to 0.95. To envisage the characteristics of fluid flow and heat transfer, two different models, namely, Darcy Extended Forchheirmer (DEF) and Local thermal non-equilibrium, have been incorporated for the metal foam region. The numerical results are compared with experimental and analytical results available in the literature for the purpose of validation. The results of the parametric studies on vertical channel show that the Nusselt number increases with the increase of partial filling of metal foams. The thermal performance of the metal foams is reported in terms of Colburn j and performance factors. © Copyright 2018 by ASME.Item Comparison of fluid flow and heat transfer through metal foams and wire mesh by using CFD(Bentham Science Publishers, 2019) Kotresha, B.; Gnanasekaran, N.Background: The unique structural characteristics of the metal foams, such as low density, large surface area, ability to increase turbulence, and increased heat transfer efficiency, are the advantages associated with thermal applications such as electronics cooling, refrigeration air conditioning, etc. The porous metal foam structures are extensively used to enhance heat transfer. Objective: This paper discusses the numerical simulations of a vertical channel filled with metal foam and wire mesh. The fluid flow and heat transfer phenomena of a wire mesh are compared with two different types of metal foams. Metal foams are made of aluminium and copper while the wire mesh is made of brass. The porosity of the metallic porous structures varies from 0.85 to 0.95. Methods: A Darcy extended Forchheirmer model is considered for solving fluid flow through the porous media while the heat transfer through the porous media is predicted using local thermal non-equilibrium model. Results: Initially, the results obtained using the proposed numerical procedures are compared with experimental results available in the literature. The numerical simulations suggest that the pressure drop increases as the velocity of the fluid increases and decreases as the porosity increases. The heat transfer coefficient and Nusselt number are determined for both the metal foams and the wire mesh. Conclusion: The Nusselt number obtained for wire mesh shows almost 90% of the copper metal foam in the same porosity range. The numerical results suggest that the brass wire mesh porous medium can also be used for enhancement of heat transfer. In this article, patents have been discussed. © 2019 Bentham Science Publishers.Item Effect of thickness and thermal conductivity of metal foams filled in a vertical channel – a numerical study(Emerald Publishing, 2019) Kotresha, B.; Gnanasekaran, N.Purpose: This paper aims to discuss about the two-dimensional numerical simulations of fluid flow and heat transfer through high thermal conductivity metal foams filled in a vertical channel using the commercial software ANSYS FLUENT. Design/methodology/approach: The Darcy Extended Forchheirmer model is considered for the metal foam region to evaluate the flow characteristics and the local thermal non-equilibrium heat transfer model is considered for the heat transfer analysis; thus the resulting problem becomes conjugate heat transfer. Findings: Results obtained based on the present simulations are validated with the experimental results available in literature and the agreement was found to be good. Parametric studies reveal that the Nusselt number increases in the presence of porous medium with increasing thickness but the effect because of the change in thermal conductivity was found to be insignificant. The results of heat transfer for the metal foams filled in the vertical channel are compared with the clear channel in terms of Colburn j factor and performance factor. Practical implications: This paper serves as the current relevance in electronic cooling so as to open up more parametric and optimization studies to develop new class of materials for the enhancement of heat transfer. Originality/value: The novelty of the present study is to quantify the effect of metal foam thermal conductivity and thickness on the performance of heat transfer and hydrodynamics of the vertical channel for an inlet velocity range of 0.03-3 m/s. © 2018, Emerald Publishing Limited.Item A Synergistic Combination of Thermal Models for Optimal Temperature Distribution of Discrete Sources Through Metal Foams in a Vertical Channel(American Society of Mechanical Engineers (ASME) infocentral@asme.org, 2019) Kotresha, B.; Gnanasekaran, N.This paper discusses about the numerical prediction of forced convection heat transfer through high-porosity metal foams with discrete heat sources in a vertical channel. The physical geometry consists of a discrete heat source assembly placed at the center of the channel along with high thermal conductivity porous metal foams in order to enhance the heat transfer. The novelty of the present work is the use of combination of local thermal equilibrium (LTE) model and local thermal nonequilibrium (LTNE) model for the metal foam region to investigate the temperature distribution of the heat sources and to obtain an optimal heat distribution so as to achieve isothermal condition. Aluminum and copper metal foams of 10 PPI having a thickness of 20 mm are considered for the numerical simulations. The metal foam region is considered as homogeneous porous media and numerically modeled using Darcy Extended Forchheimer model. The proposed methodology is validated using the experimental results available in literature. The results of the present numerical solution indicate that the excess temperature of the bottom heat source reduces by 100 °C with the use of aluminum metal foam. The overall temperature of the vertical channel reduces based on the combination of LTE and LTNE models compared to only LTNE model. The results of excess temperature for both the empty and the metal foam filled vertical channels are presented in this work. © 2019 by ASME.Item Determination of interfacial heat transfer coefficient for the flow assisted mixed convection through brass wire mesh(Elsevier Masson SAS 62 rue Camille Desmoulins Issy les Moulineaux Cedex 92442, 2019) Kotresha, B.; Gnanasekaran, N.In this work, a numerical investigation of Darcy?Forchheimer mixed convection from a heated vertical flat plate embedded in a brass wire mesh porous medium is carried out to determine the coupled effects of flow and thermal diffusion. The numerical model consists of a two dimensional computational domain in which conjugate heat transfer analysis is performed to predict the hydrodynamic and thermal performance of the brass wire mesh in a vertical channel using Local Thermal Non-Equillibrium (LTNE) model. The novelty of the present study is to acquire the interfacial heat transfer coefficient, an as yet another challenging task, of the wire mesh porous medium so as to provide a quick and feasible solution to modeling of fluid flow and heat transfer through brass wire mesh porous media. The results of heat transfer through brass wire mesh are reported in terms of Colburn j factor, performance factor and are compared with other porous mediums available in literature. The present study not only opens up new vistas for more parametric studies but also provides practical and cost effective assessment to design new porous materials. © 2018 Elsevier Masson SASItem 3D coupled conduction-convection problem using in-house heat transfer experiments in conjunction with hybrid inverse approach(Emerald Group Holdings Ltd., 2019) Vishweshwara, P.S.; Kumar, M.K.; Gnanasekaran, N.; Mahalingam, A.Purpose: Many a times, the information about the boundary heat flux is obtained only through inverse approach by locating the thermocouple or temperature sensor in accessible boundary. Most of the work reported in literature for the estimation of unknown parameters is based on heat conduction model. Inverse approach using conjugate heat transfer is found inadequate in literature. Therefore, the purpose of the paper is to develop a 3D conjugate heat transfer model without model reduction for the estimation of heat flux and heat transfer coefficient from the measured temperatures. Design/methodology/approach: A 3 D conjugate fin heat transfer model is solved using commercial software for the known boundary conditions. Navier–Stokes equation is solved to obtain the necessary temperature distribution of the fin. Later, the complete model is replaced with neural network to expedite the computations of the forward problem. For the inverse approach, genetic algorithm (GA) and particle swarm optimization (PSO) are applied to estimate the unknown parameters. Eventually, a hybrid algorithm is proposed by combining PSO with Broyden–Fletcher–Goldfarb–Shanno (BFGS) method that outperforms GA and PSO. Findings: The authors demonstrate that the evolutionary algorithms can be used to obtain accurate results from simulated measurements. Efficacy of the hybrid algorithm is established using real time measurements. The hybrid algorithm (PSO-BFGS) is more efficient in the estimation of unknown parameters for experimentally measured temperature data compared to GA and PSO algorithms. Originality/value: Surrogate model using ANN based on computational fluid dynamics simulations and in-house steady state fin experiments to estimate the heat flux and heat transfer coefficient separately using GA, PSO and PSO-BFGS. © 2019, Emerald Publishing Limited.