The paper deals with the numerical investigation of natural and mixed convection heat transfer on optimal distribution of five non-identical protruding discrete heat sources (Aluminium) mounted on a substrate (Bakelite) board. The heat sources are subjected to a uniform heat flux of 2000 W/m2. The temperature of heat sources along with the effect of thermal interaction between them is predicted by carrying out numerical simulations using ANSYS Icepak, and the results are validated with the existing experimental findings. The results suggest that mixed convection is a better method for cooling of discrete heat source modules. Also, the temperature of heat sources is a strong function of their shape, size, and positioning on the substrate. Effect of radiation is studied by painting the surface of heat sources by black paint. The results conclude that, under natural convection heat transfer, the temperature of heat sources drops by 6-13% from polished to black painted surface, while mixed convection results in the drop by 3-15%. The numerical predictions are in strong agreement with experimental results. © 2017 Published under licence by IOP Publishing Ltd.

Tapano Kumar Hotta

School of Mechanical Engineering

Vellore Campus

Karvinkoppa M.V

Fulltext

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Numerical investigation of natural and mixed convection heat transfer on optimal distribution of discrete heat sources mounted on a substrate

IOP Conference Series: Materials Science and Engineering

The paper aims at the transient numerical modelling under mixed convection for the cooling of seven protruding asymmetric IC chips mounted on an SMPS board using the phase change material (n-eicosane). The phase change material (PCM) is kept inside the mini-channels fabricated on the board. The objective is to bring down the temperature (minimize the maximum temperature) of the configuration (SMPS board with 7 IC chips) using the n-eicosane inside the mini-channels. It is seen that n-eicosane absorbs the heat dissipated by the IC chips and thus the maximum temperature of the configuration reduces by 5.5%. The effect of channel hydraulic diameter (2.5 mm ≤ Dh ≤ 3.5 mm) on the temperature of the IC chips is also studied. The results suggest that the mini-channel with lower hydraulic diameter gives a better rate of heat transfer from the IC chips and thus cools these effectively. The study is extended using four different phase change materials out of which, n-eicosane has resulted in maximum temperature drop from the IC chips among different PCMs due to its lower melting point value. A correlation is proposed for the non-dimensional temperature (θ) of the IC chips in terms of Fourier number (Fo) to predict the IC chip temperatures during the melting of PCM. © 2019 Elsevier Ltd

Journal of Energy Storage

Role of PCM based mini-channels for the cooling of multiple protruding IC chips on the SMPS board - A numerical study

IEEE Transactions on Components, Packaging and Manufacturing Technology

Introducing IEEE Collabratec

Proceeding of First Thermal and Fluids Engineering Summer Conference

A NUMERICAL AND EXPERIMENTAL STUDY OF OPTIMAL DISTRIBUTION OF DISCRETE HEAT SOURCE ARRAY COOLED BY NATURAL AND FORCED CONVECTION

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. © 2014 Taylor & Francis Group, LLC.

Experimental Heat Transfer

Experiment driven ANN-GA based technique for optimal distribution of discrete heat sources under mixed convection

Experiments have been conducted from five protruding rectangular discrete heat sources (aluminum) of non-identical sizes arranged at different positions on a substrate board (Bakelite), under natural convection, to determine their optimal configuration. A substrate board is designed for conducting experiments on multiple configurations of heat sources using the same board. A heuristic non-dimensional geometric parameter, is defined for the purpose of identifying the optimal configuration for which the maximum temperature excess among the five heat sources of a configuration is the minimum, among all possible configurations. The maximum temperature excess is found to decrease with, so the configuration with highest is deemed to be the optimal one. The effect of surface radiation on the heat transfer rate from the heat sources is studied by painting their surfaces with black paint of high emissivity, which reduces their temperature by as much as 15%. An empirical correlation is developed for the non-dimensional maximum temperature excess (θ) in terms of, taking into account the effect of radiation. To minimize the error between the temperatures obtained by prediction (correlation) and experiment, and to determine the global optimal configuration of heat sources more rigorously, an artificial neural network (ANN) is trained using the experimental data, which then powers the genetic algorithm (GA) code. © 2015 Taylor and Francis Group, LLC.

Journal	Data powered by TypesetIOP Conference Series: Materials Science and Engineering
Publisher	Data powered by TypesetIOP Publishing
ISSN	1757-8981
Open Access	Yes