Comparison of Kinetic-based and Artificial Neural Network Modeling Methods for a Pilot Scale Vacuum Gas Oil Hydrocracking Reactor
Comparison of Kinetic-based and Artificial Neural Network Modeling Methods for a Pilot Scale Vacuum Gas Oil Hydrocracking Reactor
复制标题
中试减压瓦斯油加氢裂化反应器基于动力学和人工神经网络建模方法的比较
DOI：
10.9767/bcrec.8.2.4722.125-136
复制
发表时间：
2013
影响因子：
1.5
通讯作者：
G. Zahedi
中科院分区：
文献类型：
--
作者：
S. Sadighi;G. Zahedi
介绍了一个中试规模的真空瓦斯油加氢裂化装置的人工神经网络模型和动力学模型。使用文献中报告的实验数据来开发、训练和检查这些模型。所建立的模型能够预测所有主要加氢裂化产物的产率，包括干气、轻石脑油、重石脑油、煤油、柴油和未转化的VGO（残留物）。结果表明，基于动力学模型和人工神经模型对加氢裂化产物产率的预测能力较强。前者能够准确预测轻质石脑油、重质石脑油和煤油等轻质产品的产率。而人工神经网络模型对柴油和渣油产量的预测精度较高。对比表明，人工神经网络模型优于基于动力学的模型。©2013 bcrec undip。接收日期：2013年4月9日；2013年8月13日修订；收录日期：2013年8月18日[出处：Sadighi， S., Zahedi， G.R.(2013)]。中试减压气油加氢裂化反应器动力学建模与人工神经网络建模方法的比较化学反应工程与催化，8(2):125-136。[doi:10.9767/bcrec.8.2.4722.125-136] [Permalink/ doi: http://dx.doi.org/10.9767/bcrec.8.2.4722.125-136]
An artificial neural network (ANN) and kinetic-based models for a pilot scale vacuum gas oil (VGO) hydrocracking plant are presented in this paper. Reported experimental data in the literature were used to develop, train, and check these models. The proposed models are capable of predicting the yield of all main hydrocracking products including dry gas, light naphtha, heavy naphtha, kerosene, diesel, and unconverted VGO (residue). Results showed that kinetic-based and artificial neural models have specific capabilities to predict yield of hydrocracking products. The former is able to accurately predict the yield of lighter products, i.e. light naphtha, heavy naphtha and kerosene. However, ANN model is capable of predicting yields of diesel and residue with higher precision. The comparison shows that the ANN model is superior to the kinetic-base models. © 2013 BCREC UNDIP. All rights reserved Received: 9th April 2013; Revised: 13rd August 2013; Accepted: 18th August 2013 [ How to Cite : Sadighi, S., Zahedi, G.R. (2013). Comparison of Kinetic-based and Artificial Neural Network Modeling Methods for a Pilot Scale Vacuum Gas Oil Hydrocracking Reactor. Bulletin of Chemical Reaction Engineering & Catalysis , 8 (2): 125-136. (doi:10.9767/bcrec.8.2.4722.125-136)] [ Permalink/DOI : http://dx.doi.org/10.9767/bcrec.8.2.4722.125-136 ]