Faculty Publications
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Item Condensation heat transfer and pressure drop of R-134a saturated vapour inside a brazed compact plate fin heat exchanger with serrated fin(Springer Verlag service@springer.de, 2017) Ramana Murthy, K.V.; Chennu, C.; Ashok Babu, T.P.This paper presents the experimental heat transfer coefficient and pressure drop measured during R-134a saturated vapour condensation inside a small brazed compact plate fin heat exchanger with serrated fin surface. The effects of saturation temperature (pressure), refrigerant mass flux, refrigerant heat flux, effect of fin surface characteristics and fluid properties are investigated. The average condensation heat transfer coefficients and frictional pressure drops were determined experimentally for refrigerant R-134a at five different saturated temperatures (34, 38, 40, 42 and 44 °C). A transition point between gravity controlled and forced convection condensation has been found for a refrigerant mass flux around 22 kg/m2s. In the forced convection condensation region, the heat transfer coefficients show a three times increase and 1.5 times increase in frictional pressure drop for a doubling of the refrigerant mass flux. The heat transfer coefficients show weak sensitivity to saturation temperature (Pressure) and great sensitivity to refrigerant mass flux and fluid properties. The frictional pressure drop shows a linear dependence on the kinetic energy per unit volume of the refrigerant flow. Correlations are provided for the measured heat transfer coefficients and frictional pressure drops. © 2016, Springer-Verlag Berlin Heidelberg.Item Flow boiling heat transfer and pressure drop analysis of R134a in a brazed heat exchanger with offset strip fins(Springer Verlag service@springer.de, 2017) Amaranatha Raju, M.; Ashok Babu, T.P.; Chennu, C.The saturated flow boiling heat transfer and friction analysis of R 134a were experimentally analyzed in a brazed plate fin heat exchanger with offset strip fins. Experiments were performed at mass flux range of 50–82 kg/m2 s, heat flux range of 14–22 kW/m2 and quality of 0.32–0.75. The test section consists of three fins, one refrigerant side fin in which the boiling heat transfer was estimated and two water side fins. These three fins are stacked, held together and vacuum brazed to form a plate fin heat exchanger. The refrigerant R134a flowing in middle of the test section was heated using hot water from upper and bottom sides of the test section. The temperature and mass flow rates of water circuit is controlled to get the outlet conditions of refrigerant R134a. Two-phase flow boiling heat transfer and frictional coefficient was estimated based on experimental data for offset strip fin geometry and presented in this paper. The effects of mass flux, heat flux and vapour quality on heat transfer coefficient and pressure drop were investigated. Two-phase local boiling heat transfer coefficient is correlated in terms of Reynolds number factor F, and Martinelli parameter X. Pressure drop is correlated in terms of two-phase frictional multiplier ?f, and Martinelli parameter X. © 2017, Springer-Verlag Berlin Heidelberg.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 Inverse approach for estimating boundary properties in a transient fin problem(Springer, 2018) Gnanasekaran, N.; Balaji, S.A solution methodology is proposed for an inverse estimation of boundary conditions from the knowledge of transient temperature data. A forward model based on prevalent time-dependent heat conduction fin equation is solved using a fully implicit finite volume method. First, the inverse model is formulated and accomplished for time-invariant heat flux at the fin base, and later extended to transient heat flux, base temperature and average heat transfer coefficient. Secondly, the Nusselt number is then replaced with Rayleigh number in the forward model to realistically estimate the base temperature, which varies with respect to time, based on in-house transient fin heat transfer experiments. This scenario further corroborates the validation of the proposed inverse approach. The experimental set-up consists of a mild steel 250×150×6mm3 fin mounted centrally on an aluminium base 250×150×8mm3 plate. The base is attached to an electrical heater and insulated with glass-wool to prevent heat loss to surroundings. Five calibrated K-type thermocouples are used to measure temperature along the fin. The functional form of the unknown parameters is not known beforehand; sensitivity studies are performed to determine suitability of the estimation and location of sensors for the inverse approach. Conjugate gradient method with adjoint equation is chosen as the inverse technique and the study is performed as a numerical optimization; subsequently, the estimates show satisfactory results. © 2018, Indian Academy of Sciences.Item 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 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 Investigation of flow boiling heat transfer and pressure drop of R134a in a rectangular channel with wavy fin(Elsevier Masson SAS 62 rue Camille Desmoulins Issy les Moulineaux Cedex 92442, 2020) Amaranatha Raju, M.; Ashok Babu, T.P.; Chennu, C.The saturated flow boiling heat transfer and pressure drop studies of R134a were experimentally investigated in a rectangular channel with wavy fin. Experiments were performed at mass flux range 30–50 kg m?2 s?1, heat flux range 11–18 kW m?2 and quality 0.26–0.8. The experimental data were obtained in a brazed test section. In preliminary step, single phase experiments were conducted to find out the j and f data of the wavy fin. In second step, two-phase flow boiling experiments were conducted to estimate the heat transfer and frictional coefficient based on experimental data. The trends of heat transfer and pressure drop with respect to mass flux, heat flux and quality were studied. Two-phase local boiling heat transfer coefficient is correlated in terms of Reynolds number factor F, and Martinelli parameter X. Pressure drop is correlated in terms of two-phase frictional multiplier, ?f and Martinelli parameter, X. © 2019 Elsevier Masson SASItem 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 Numerical analysis of multiple phase change materials based heat sink with angled thermal conductivity enhancer(Elsevier Ltd, 2022) Nedumaran, M.; Gnanasekaran, G.; Hooman, K.Phase change materials (PCM) RT-28HC, RT-35HC, and RT-44HC with three different melting temperatures, 29 °C, 36 °C, and 44 °C, with similar thermal properties, are considered. The PCM is oriented from the left to right side of the heat sink in its increasing order. The fins are attached to the heat sink longitudinally, and its orientation effects are studied low (100–500 W/m2) and high (1000–5000 W/m2) heat fluxes applied on the horizontal bottom surface of the heat sink. A 2D model is developed using ANSYS Fluent 19, and the fin orientation effects are investigated numerically. The orientation of fins at different angles such as 0°, +15°, +30°, +45°, +60°,-15°,-30°,-45°, −60° are considered. The effect of fins on the charging cycle is assessed by comparing a single and double PCM heat sink. Three initial conditions are investigated by altering the initial temperature 300 K, 303 K, and 310 K. At increasing heat input, the negative angled fins possess a higher melting rate. For different initial conditions, −60° provides higher enhancement, and +60° possesses prolonged melting for almost all cases. The performance of a triple PCM design is compared with single and double PCM counterparts under similar conditions. © 2022 The Authors