四喷嘴对置式气化炉停留时间分布的随机模型

Stochastic model of residence time distribution in opposed tetra-burner gasifier

运用连续时间马尔可夫链及矩阵相关理论,建立了停留时间分布随机模型。根据对四喷嘴对置式气化炉流场的测试,将气化炉划分为若干区域,并且对各个区域体积进行了估算,组成马尔可夫链状态转移图。模拟计算表明,当射流回流区和撞击流回流区回流比为1,管流区为平推流模式,其他区域按全混流模式处理时,模拟值与实验值较接近。用优化的模型计算了不同条件的冷模气化炉的停留时间分布,结果表明,随着气体流量的增大,平均停留时间减小,无因次方差增大;随着炉体高度的增加,平均停留时间增大,无因次方差减小。对工业气化炉停留时间分布进行了预测,炉内流型总体上趋近于全混流,有利于炉内的气化反应。

A stochastic model of the residence time distribution was established on the basis of a continuous-time Markov chain and some knowledge of matrix. According to the measurement of flow field for the opposed tetraburner gasifier, the gasifier was divided into several regions and the Markov chain states transfer diagram was formed. It is found that the calculated results can give a reasonable fit for the experimental data when the reflux ratio of jet reflux region and impinging stream reflux region is 1, and the tube stream region can be regarded as PFR, the other regions as CSTR. Based on the established model, the residence time distribution of cold model gasifier for different conditions is predicted. It can be concluded that the mean residence time is reduced and the variance is increased with the increase of flow rate. The mean residence time is increased and the variance is reduced with the increase of gasifier height. The prediction of residence time distribution for an industrial opposed tetra-burner gasifier shows that the flow pattern of industrial gasifier is closed to CSTR, which is beneficial to the gasification reaction.