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Identification of Convection Heat Transfer Coefficient Parameters Based on Hybrid Particle Swarm Algorithm in the Secondary Cooling Zone for Steel Continuous Casting Process

机译:基于混合粒子群算法在钢连铸过程中的混合粒子群算法的对流传热系数参数识别

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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.
机译:基于钢连铸方法的控制体积法开发凝固模型,其是非线性和非差异的,并且确定了二次冷却区的每个段的对流传热系数的参数,一种新的混合粒子群算法(CPSO)介绍通过将混沌搜索嵌入粒子群体算法中的混沌搜索来提高优化性能。它用于根据坯料表面温度和壳厚度识别对流传热系数。与经验公式方法相比,它与Trail数据更好地协议。

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