摘要
Kumar模型是反映石脑油裂解过程的分子动力学模型,其一次反应选择性系数随原料油品的不同而改变,对模型的精度有很大影响。由于裂解过程复杂,很难找到实用的规律对它进行预测,往往需要通过化工实验来对其进行测定。文章设计了一种随机搜索算法,利用油品特性和生产数据,对Kumar模型的一次反应选择性进行调整。文中对算法的设计进行了详细描述,仿真结果表明,由这个算法可以得到比较理想的结果。
The selectivities of the first reaction in Kumar model are not always kept constant when the detailed com-position of raw material is changed.The Kumar model's precision is influenced remarkably by these selectivities.It's diffi-cult to find a general way to predict them due to the complexity of the pyrolysis process.A stochastic searching method is bring forward here to predict the selectivities based on the characteristics of the raw material and the experimental data.The simulation results agree with the experimental data well with the selectivities get by this method.
出处
《计算机工程与应用》
CSCD
北大核心
2003年第32期10-12,21,共4页
Computer Engineering and Applications
基金
国家863高技术发展研究计划/CIMS主题支持(编号:2001AA413320)
