Arun Shori

Bio: Arun Shori is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Computational fluid dynamics & Combined forced and natural convection. The author has an hindex of 1, co-authored 1 publications receiving 18 citations.

Optimal Heat Distribution Among Discrete Protruding Heat Sources in a Vertical Duct: A Combined Numerical and Experimental Study

Abstract: This paper reports the results of experimental and numerical investigations of optimal heat distribution among the protruding heat sources under laminar conjugate mixed convection heat transfer in a vertical duct. A printed circuit board with 15 heat sources forms a wall of a,duct. Three-dimensional governing equations of flow and heat transfer were solved in the flow domain along with the energy equation in the solid domain using FLUENT 6 . 3 . A database of temperatures of each of the heat sources for different heat distributions is generated numerically. Artificial neural networks (ANNs) were used as a forward model to replace the time consuming complex computational fluid dynamics (CFD) simulations. The functional relationship between heat input distribution and the corresponding temperatures of the heat sources obtained by training the network is used to drive a genetic algorithm based optimization procedure to determine the optimal heat distribution. The optimal distribution here refers to the apportioning of a fixed quantity of heat among 15 heat sources, keeping the maximum of the temperatures of the heat sources to a minimum. Furthermore, the heat distribution corresponding to a set of specified target temperatures of the heat sources is obtained using a network that is trained and tested with a database of temperatures of the heat sources generated using FLUENT 6.3 in the range of total heat dissipation of 5-25 W. Using this network, it was possible to maximize the total heat dissipation from the heat sources for a given target temperature directly. In order to validate the optimization method, a low speed vertical wind tunnel has been used to carry out the mixed convection experiments for different combinations of heat distribution and also for the optimal heat distribution, and the temperatures of the heat sources were measured. The results of the numerical simulations, ANN, and the corresponding experimental results are in good agreement.

Literature Survey of Numerical Heat Transfer (2010-2011)

Abstract: Here a comprehensive survey of the literature in the area of numerical heat transfer (NHT) published in 2010 and 2011 has been conducted. Due to the immenseness of the literature volume, journals s...

Experiment Driven Ann-GA Based Technique for Optimal Distribution of Discrete Heat Sources Under Mixed Convection

Abstract: This article reports the results of mixed convection heat transfer studies from five heat sources (aluminum) mounted at different positions on a substrate board (Bakelite). The goal is to determine the optimal arrangement, such that, the maximum temperature excess is minimum among all the possible configurations. For accomplishing this, a completely experimental driven hybrid optimization strategy, that combines Artificial neural network (ANN) with Genetic algorithm (GA) is used. Initial optimization studies are carried out by employing a heuristic non-dimensional geometric parameter λ, which is identified to be the key parameter to decide the maximum temperature in the system.

Effect of surface radiation heat transfer on the optimal distribution of discrete heat sources under natural convection

Abstract: Experiments have been conducted for natural convection heat transfer from protruding discrete heat sources, mounted at different positions on a substrate, to determine the optimal configuration, and to study the effect of surface radiation on them, which reduces their temperature upto 12 %. The optimal configuration has been determined by a non-dimensional geometric distance parameter (λ). An empirical correlation has been proposed between the non-dimensional steady state temperature (θ) and λ, by taking into account the effect of surface radiation heat transfer.