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化学工业与工程 2018, Vol. 35 Issue (1) :69-74    DOI: 10.13353/j.issn.1004.9533.20161089
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悬浮床加氢反应器壁面的结焦预测
张晓1, 姜斌1,2, 肖晓明1
1. 天津大学化工学院, 天津 300072;
2. 精馏技术国家工程研究中心, 天津 300072
Prediction of the Coking on the Wall of the Suspended Bed Reactor for Hydrogenation Reaction
Zhang Xiao1, Jiang Bin1,2, Xiao Xiaoming1
1. School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China;
2. National Engineering Research Centre of Distillation Technology, Tianjin 300072, China

摘要
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摘要 

以1个空桶结构的悬浮床加氢反应器为研究对象,首先采用计算流体力学模拟软件来模拟其内部流动场,然后通过MATLAB中的BP神经网络模型以及数据拟合软件对实验数据进行拟合,得到结焦率与反应条件之间的关系式。最后将得到的关系式作为变量插入到计算流体力学后处理软件中进行分析,观察各个壁面处的coke值分布图,并结合内部速度场分布判断易结焦位置。结果表明,在此模型中易结焦位置集中在反应器底部中间位置、分配盘上表面中心区域以及分配盘与反应器主体壁面的连接处。

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张晓
姜斌
肖晓明
关键词悬浮床反应器   BP神经网络   结焦率     
Abstract

Choosing a suspended bed hydrogenation reactor with a simple structure as an object, the computational fluid dynamics software was used to simulate the internal fluid flow in it. The BP neural network model in the MATLAB and the data fitting software were used to calculate the experiment data, and finally got the relation formula between the coke yield and the reaction data. The relation formula was used as a variable to insert into the simulation result files of CFD-post. Finally the contour of the coking data can be seen directly from the wall, combining with the internal flow field, the easy-coking position can be estimated. The result shows that, in this model, the easy-coking positions concentrated on the middle on the bottom, the central region of the upper surface on the distribution tray and joint of the tray and the wall.

Keywordssuspended bed reactor;   BP neural network;   coke yield     
Received 2016-04-29;
Corresponding Authors: 肖晓明,E-mail:xmxiao@tju.edu.cn。     Email: xmxiao@tju.edu.cn
About author: 张晓(1992-),女,硕士研究生,现从事计算流体力学模拟方面的研究。
引用本文:   
张晓, 姜斌, 肖晓明.悬浮床加氢反应器壁面的结焦预测[J].  化学工业与工程, 2018,35(1): 69-74
Zhang Xiao, Jiang Bin, Xiao Xiaoming.Prediction of the Coking on the Wall of the Suspended Bed Reactor for Hydrogenation Reaction[J].  Chemcial Industry and Engineering, 2018,35(1): 69-74
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