基于混合粒子群算法的钢连铸二冷区对流换热系数参数识别

Guoshan Wu, Rong-Yang Wu
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引用次数: 3

摘要

基于控制体积法建立了钢连铸过程非线性、非微分凝固模型,确定了二冷区各段对流换热系数参数,引入混合粒子群算法(CPSO),在粒子群算法中嵌入混沌搜索,提高了优化性能。根据坯料表面温度和坯壳厚度确定对流换热系数。与经验公式法相比,该方法与实测数据具有更好的一致性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of convection heat transfer coefficient parameters based on hybrid particle swarm algorithm in the secondary cooling zone for steel continuous casting process
Solidification model is developed based on control volume method for steel continuous casting process, which is nonlinear and non-differential, and parameters of convective heat transfer coefficient for each segment of the secondary cooling zone are ascertained, a new hybrid particle swarm algorithm (CPSO) is introduced to improve the optimizing performance by embedding the chaotic search in the particles swarm algorithm. It is used to identify the convective heat transfer coefficients according to billet surface temperature and shell thickness. Compared with the empirical formula method, it has a better agreement with trail data
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