Optimization of Cooling Parameters in Casting Processes Based on Adaptive Evolutionary Particle Swarm Algorithm

Zhen Ping Ji; Yuan Yuan Jiang

doi:10.4028/www.scientific.net/AMR.468-471.2399

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 468-471Optimization of Cooling Parameters in Casting...

Optimization of Cooling Parameters in Casting Processes Based on Adaptive Evolutionary Particle Swarm Algorithm

Abstract:

The aim of this work was to develop an optimization tool consisting of a two dimensional heat transfer model and an optimization algorithm to determine the improved cooling conditions for the sprays zones of a real continuous caster. The mathematical model of cooling process was used to calculate the strand temperatures along the machine. An optimization algorithm based on an Adaptive Evolutionary Particle Swarm Optimization (AEPSO) approach was used to solve an optimal control of secondary cooling water distribution according to certain metallurgical criteria and some technological constraints, which enhance the global exploratory capability and avoid pre-mature convergence. The simulation results show that it can improve the repeatability and quality of solution.

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Periodical:

Advanced Materials Research (Volumes 468-471)

Pages:

2399-2402

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.468-471.2399

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Online since:

February 2012

Authors:

Zhen Ping Ji, Yuan Yuan Jiang

Keywords:

Adaptive Evolutionary Particle Swarm Optimization (AEPSO), Continuous Casting, Secondary Cooling Water, Two Dimensional Heat Transfer Model

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