Issue |
E3S Web of Conf.
Volume 559, 2024
2024 International Conference on Sustainable Technologies in Civil and Environmental Engineering (ICSTCE 2024)
|
|
---|---|---|
Article Number | 02001 | |
Number of page(s) | 11 | |
Section | Mechanical Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202455902001 | |
Published online | 08 August 2024 |
Design Optimization of Manifold Microchannel Heat Sink using Evolutionary Algorithms
Symbiosis Institute of Technology, Symbiosis International (Deemed University), Lavale, Pune 412115, India
* vikas.gulia@sitpune.edu.in
* aniket.nargundkar@sitpune.edu.in
In today’s world, miniaturized products are proved to be the dis-ruptive technologies contributing to the sustainability through green energy. Microchannel heat sink (MCHS) is an advanced cooling device to accom-plish the cooling requirements for such miniaturized products through sus-tainable approach. In this work, two popular Nature Inspired Swarm Intelli-gence algorithms viz. Teaching Learning Based Optimization (TLBO) and Particle swarm optimization (PSO) are applied for optimizing the perfor-mance of MCHS through maximizing the Thermal resistance & Minimizing the Pumping Power of MCHS. Results are compared with the numerical analysis and GA. For the objective function thermal resistance, results of TLBO and PSO algorithms are improved by 8 % as compared with numeri-cal solutions. For pumping power problem, significant improvement in the results viz. 90.86% is observed with TLBO and PSO algorithm respectively. This optimized design can be directly adopted and it ensures the optimized cooling through equal sharing of thermal load by every channel and thereby minimizing the pump energy consumption. This work demonstrates the ap-plicability of contemporary Nature Inspired Artificial Intelligence (AI) based algorithms in the domain of Heat Sinks and a step towards a green energy.
Key words: Microchannel Heat Exchanger / Optimization / TLBO / PSO / Heat Sink
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.