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A genetic algorithm for optimizing gravity die casting’s heat transfer coefficients

Wong, Dennis ML and Pao, William (2011) A genetic algorithm for optimizing gravity die casting’s heat transfer coefficients. Expert Systems with Applications, 38 (6). pp. 7076-7080. ISSN 09574174

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Abstract

Numerical simulation of solidification has improved our understanding of casting processes significantly 16 over the last two decades. One of the most desirable features in the design of casting of high strength 17 components is directional solidification. Generally, expertise from skilled foundry men is required during 18 the design of casting-mould assembly interrogation in order to achieve a satisfactory thermal control, 19 thus directional solidification. This process is not only costly, both financially and temporally to found- 20 ries, it also heavily rely on foundry men’s experiences. Our main aim in this project is to explore a novel 21 and fully automated computer scheme that ties the geometric features of the casting with evolutionary 22 algorithms to achieve thermal control. By extracting the medial axes of the casting geometry and corre- 23 late it with the interfacial heat transfer coefficient via evolutionary algorithm, we are able to perform 24 non-exhaustive search of the optimized solution. Preliminary results from our computer experiments 25 showed favourable results. In this paper, the focus is sharpened on the convergence and optimality of 26 the developed GA.

Item Type:Article
Impact Factor:2.193
Subjects:T Technology > TJ Mechanical engineering and machinery
Departments / MOR / COE:Departments > Mechanical Engineering
ID Code:6459
Deposited By: Dr William Pao
Deposited On:26 Sep 2011 09:36
Last Modified:19 Jan 2017 08:22

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