Design and Optimisation of Pressure Vessel Using Metaheuristic Approach

Abstract:

The objective of design optimization of pressure vessels is cost reduction by reducing weight with adequate strength and stiffness. Optimization is the act of obtaining the best result under given circumstances. Conventional design aims at finding acceptability design which merely satisfies the functional and other requirements of the problem. In general, there will be more than one acceptable designs and the purpose of design optimization is to choose the best. In the present work parameters such as thickness of the shell, and dish end, length and radius of the pressure vessel are optimized by making use of ACO has been shown for a Pressure vessel problem with four variables and four design constraints. It is found that the results obtained from ACO are better as its search is for global optimum as against the local optimum in traditional search methods. The results of the ACO have been checked using ANSYS, and it is found to perform satisfactorily.

• Periodical: Applied Mechanics and Materials (Volumes 465-466)
• Pages: 401-406
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.465-466.401
• Online since: December 2013
• Authors: Sulaiman Hassan, Kavi Kumar, Ch Deva Raj, Kota Sridhar
• Keywords: Ant Colony Optimization Algorithm, Design Optimization, Pressure Vessels

References

[1] GUO Chuang-xin, HU Jia-sheng , YE Bin , CAO Yi-jia, Swarm Intelligence For Mixed-Variable Design Optimization, Journal of Zhejiang University SCIENCE ISSN 1009-3095.

[2] Tae-Hwan Joung, In-Sik Nho, Chong-Moo Lee, Pan-Mook Lee, Seung-Il Yang, Seok-Won Hong A Study on the Pressure Vessel Design, Structural Analysis and Pressure Test of a 6, 000 m Depth-rated Unmanned Underwater Vehicle, the International society of Offshore and Polar Engineers ISBN 1-880653-64-8.

DOI: 10.1080/17445300802204371

[3] Michael A. Porter, Dennis H. Martens, Pedro Marcal On Using Finite Element Analysis for Pressure Vessel Design, PVP Vol. 368, ASME, New York, NY, pp.139-146.

[4] Xiaohui Hu, Russell C. Ebrthart, Yuhui Shi Engineering Optimization with particle Swarm, Purdue University, Simulation, vol. 62, no. 4, pp.242-254, (1994).

[5] Alaya, C. Solnon, K. Gh´edira, Ant algorithm for the multi-dimensional knapsack problem, Proceedings of International Conference on Bioinspired Optimization Methods, their Applications (BIOMA 2004), 2004, pp.63-72.

[6] Osvaldo G´omez and Benjam´ın Bar´ Omicron ACO. A New Ant Colony Optimization Algorithm , a CLEI ELECTRONIC JOURNAL, VOLUME 8, NUMBER 1, PAPER 5, AUGUST (2005).

[7] Karl O. Jones, André Bouffet comparison of bee's algorithm, ant colony Optimization and particle swarm optimization for pid Controller tuning" International Conference on Computer Systems and Technologies - CompSysTech, 08.

DOI: 10.1145/1500879.1500912