Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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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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    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.