摘要
乙烯裂解炉辐射段的过程模拟,一般由管内反应过程模型与管外传热模型两部分组成,具有非线性、强耦合的特点。其中管外传热模型涉及变量参数众多、求解过程耗时长。针对这一问题,提出了一种智能混合建模方法,在构建基于区域法的管外传热计算模型的基础上,利用该模型产生的数据,设计构造了针对管外传热计算的神经网络模型。利用该模型与管内反应过程模型相耦合,实现对乙烯裂解炉辐射段的智能混合建模与模拟。结合工业实际算例,验证了基于机器学习和机理模型的智能混合建模的可行性,裂解产物预测精度良好,且混合模型可以大大缩短计算时间,更加符合工业计算的要求。
Simulation of naphtha pyrolysis in industrial ethylene cracking furnaces,which usually requires bothfirebox and reactor models,is non-linear and strongly compounded.The firebox model involves a great number ofvariables and takes a lot of time to get a solution.An intelligent hybrid model was proposed by first designing anartificial neural network(ANN)from data of the firebox model and then combining ANN with the reactor model.The intelligent hybrid modelling and simulation was developed on an industrial ethylene cracking furnace.By usingactual process data,it is demonstrated that the hybrid simulation shows good agreement with industrial production.The hybrid model significantly reduces simulation time and largely meets requirement of industrial modeling.
作者
华丰
方舟
邱彤
HUA Feng;FANG Zhou;QIU Tong(Department of Chemical Engineering, Tsinghua University, Beijing 100084, China)
出处
《化工学报》
EI
CAS
CSCD
北大核心
2018年第3期923-930,共8页
CIESC Journal
基金
国家自然科学基金项目(U1462206)~~
关键词
模拟
模型简化
热解
神经网络
乙烯
区域法
simulation
model reduction
pyrolysis
neural network
ethylene
zone method