Faculty Publications
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Item Experimental and numerical investigation on conjugate effects in deep parallel microchannel using tio2 nanofluid for electronic cooling(Dalian University of Technology, 2018) Narendran, G.; Gnanasekaran, N.; Arumuga Perumal, D.A.The present study reports the numerical investigation of laminar forced convection based on TiO2 nanofluid in a rectangular copper microchannel surrounded by Aluminium block to examine the cooling effects for increased flow rates and particle concentration. The analysis involves the use of pure fluid and TiO2 nanofluid with the volume fractions of 0.01, 0.15, 0.20 and 0.25% for different flow rates. The study also examines the influence of conjugate heat transfer behavior of the microchannel using commercially available software FLUENT-15. © 2018 by the authors of the abstracts.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 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 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 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 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.Item Numerical Simulations of Flow-Assisted Mixed Convection in a Vertical Channel Filled with High Porosity Metal Foams(Taylor and Francis Ltd., 2020) Kotresha, B.; Gnanasekaran, N.; Balaji, C.In this work, two-dimensional numerical simulations of flow-assisted mixed convection in a vertical channel filled with high porosity metal foams have been carried out by using the commercial ANSYS FLUENT. In order to enhance heat transfer, the vertical channel is filled with aluminum metal foams of different pores per inch (PPI). Four different metal foams PPI 10, 20, 30, and 45, with porosity values varying from 0.90 to 0.95 are considered in this study. The geometry under consideration consists of metal foam attached to the aluminum plate in the vertical channel and the resulting problem becomes conjugate heat transfer. The metal foam region is considered as a homogeneous porous medium with the Darcy Extended Forchheirmer model to evaluate the flow characteristics while the local thermal non-equilibrium heat transfer model is considered for the heat transfer analysis. Initially, numerical results are compared with the experimental results available in literature and the agreement was found to be good. Parametric studies show that as the metal foam PPI increases, the pressure drop increases, while the heat transfer is seen to increase with an increase in the pore density of the metal foam. © 2019, © 2019 Taylor & Francis Group, LLC.Item 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.