Modified molecular matrix model for predicting molecular composition of naphtha

doi:10.1016/j.cjche.2017.01.008

Chinese Journal of Chemical Engineering ›› 2017, Vol. 25 ›› Issue (12): 1856-1862.DOI: 10.1016/j.cjche.2017.01.008

• 第25届中国过程控制会议专栏 • 上一篇下一篇

Modified molecular matrix model for predicting molecular composition of naphtha

Kun Wang, Shiyu Li

School of Chemical Engineering and Technology, Tianjin University, Tianjin 300354, China

收稿日期:2016-09-22 修回日期:2016-12-22 出版日期:2017-12-28 发布日期:2018-01-18
通讯作者: Shiyu Li,E-mail address:shyli@tju.edu.cn.
基金资助:
Supported by the National Natural Science Foundation of China (U1462206).

Modified molecular matrix model for predicting molecular composition of naphtha

Kun Wang, Shiyu Li

School of Chemical Engineering and Technology, Tianjin University, Tianjin 300354, China

Received:2016-09-22 Revised:2016-12-22 Online:2017-12-28 Published:2018-01-18
Contact: Shiyu Li,E-mail address:shyli@tju.edu.cn.
Supported by:
Supported by the National Natural Science Foundation of China (U1462206).

摘要/Abstract

摘要： To improve the naphtha composition prediction model based on molecular type homologous series matrix (MTHS), this paper puts forward a novelmolecular matrix to characterize the naphtha composition and the normal distribution hypothesis to better describe the molecular composition distribution within each homologous series of the molecular matrix. Through prediction calculation of eight groups of naphtha samples and eight groups of gasoline samples, it is verified that the normal distribution hypothesis is more applicable than gamma distribution hypothesis for the prediction model. According to the prediction results of the samples, the restrain range of normal distribution parameters during model computing process is summarized. With the bulk properties of naphtha samples and the value range of distribution parameters as input conditions, this study utilizes the improved novelmolecular matrix to predict the composition of naphtha samples. As the results show, the novel molecular matrix can predict more detailed composition information of naphtha and improve prediction accuracy with less unknown parameters.

关键词: MTHS molecular matrix, Distribution assumption, Naphtha, Molecular composition, Prediction model

Abstract: To improve the naphtha composition prediction model based on molecular type homologous series matrix (MTHS), this paper puts forward a novelmolecular matrix to characterize the naphtha composition and the normal distribution hypothesis to better describe the molecular composition distribution within each homologous series of the molecular matrix. Through prediction calculation of eight groups of naphtha samples and eight groups of gasoline samples, it is verified that the normal distribution hypothesis is more applicable than gamma distribution hypothesis for the prediction model. According to the prediction results of the samples, the restrain range of normal distribution parameters during model computing process is summarized. With the bulk properties of naphtha samples and the value range of distribution parameters as input conditions, this study utilizes the improved novelmolecular matrix to predict the composition of naphtha samples. As the results show, the novel molecular matrix can predict more detailed composition information of naphtha and improve prediction accuracy with less unknown parameters.

Key words: MTHS molecular matrix, Distribution assumption, Naphtha, Molecular composition, Prediction model

Kun Wang, Shiyu Li. Modified molecular matrix model for predicting molecular composition of naphtha[J]. Chinese Journal of Chemical Engineering, 2017, 25(12): 1856-1862.

Kun Wang, Shiyu Li. Modified molecular matrix model for predicting molecular composition of naphtha[J]. Chin.J.Chem.Eng., 2017, 25(12): 1856-1862.

参考文献

[1] M.I. Ahmad, N. Zhang, M. Jobson, Molecular components-based representation of petroleum fractions, Chem. Eng. Res. Des. 89 (4) (2011) 410-420.

[2] M.S. Aye, N. Zhang, A novel methodology in transformation bulk properties of refining streams into molecular information, Chem. Eng. Sci. 60 (23) (2005) 6702-6717.

[3] M. Neurock, A Computational Chemical Reaction Engineering Analysis of Complex Heavy Hydrocarbon Reaction Systems, University of Delaware, Delaware, 1992.

[4] M. Neurock, A. Nigam, D. Trauth, M.T. Klein, Molecular representation of complex hydrocarbon feedstocks through efficient characterization and stochastic algorithms, Chem. Eng. Sci. 59 (1994) 4755-4763.

[5] M. Neurock, C. Libanati, A. Nigam, Monte Carlo simulation of complex reaction systems: molecular structure and reactivity in modeling heavy oils, Chem. Eng. Sci. 45 (8) (1990) 2083-2088.

[6] K.M.V. Geem, D. Hudebine, M.F. Reyniers, Molecular reconstruction of naphtha steam cracking feedstocks based on commercial indices, Comput. Chem. Eng. 31 (9) (2007) 1020-1034.

[7] R.J. Quam, S.B. Jaffe, Structure-qriented lumping: describing the chemistry of complex hydrocarbon mixtures, Ind. Eng. Chem. Res. 3 (1992) 2483-2497.

[8] P. Ghosh, K.J. Hickey, S.B. Jaffe, Development of a detailed gasoline compositionbased octane model, Ind. Eng. Chem. Res. 45 (1) (2006) 337-345.

[9] P. Ghosh, Predicting the effect of cetane improve on disel fuels, Energy Fuel 22 (2) (2008) 1073-1079.

[10] T. Qiu, J.C. Chen, Z. Fang, Molecular reconstructionmodel for petroleum fractions based on structure oriented lumping, J. Tsinghua Univ. (Sci. Technol.) 56 (4) (2016) 424-429.

[11] L.J. Zhang, Y.G. Zhang, G.Q. Wang, Research on prediction of naphtha composition based on commercial indices, Chem. Ind. Eng. Prog. 30 (2) (2011) 278-283.

[12] B. Peng, Molecular Modeling of Petroleum Process, UMIST, Manchester, 1999.

[13] Y. Zhang, A Molecular Approach for Characterization and Property Predictions of Petroleum Mixtures with Application to Refinery Modeling(Ph.D. Thesis) Institute of Science and Technology, University of Manchester, Manchester, 1999.

[14] Y.W. Wu, N. Zhang, Molecular characterization of gasoline and diesel stream, Ind. Eng. Chem. Res. 49 (24) (2010) 12773-12782.

[15] Y.Y. Bai, S.Y. Li,MTHSmolecular matrixmodel for predictingmolecular composition of gasoline, Petrochem. Technol. 44 (12) (2015) 1433-1438.

[16] M.R. Riazi, Characterization and Properties of Petroleum Fractions, ASTM International, Philadelphia, PA, 2005.

[17] Technical Data Book-Petroleum Refining, sixth ed. American Petroleum Institute, Washington, D.C., 1997

[18] L.Y. Jiang, Estimation of the Parameters of the Generalized Gamma Distribution, Master Thesis, Southwest Jiaotong University, Chengdu, 2014.

[19] J. Wang, F. Jiao Guo, X. Zhou, Prediction of naphtha composition based on conventional physical properties, Pet. Process. Petrochem. 44 (12) (2014) 84-87.

[20] Y. Ding, M.X. Cheng, Q. Zhu, Research on method of composition prediction of naphtha based on online raman spectrometer, Transducer Microsyst. Technol. 31 (12) (2012) 69-75.

[21] Y.L. Bao, W.M.Guo, X.D. Sun, Gas chromatography assay naphtha group composition, Inn. Mong. Petrochem. Ind. 20 (3) (1999) 116-119.

[22] G. Song, T. Qiu, L. Tian, A method to predict naphtha detailed composition based on normal physical characteristics, Comput. Appl. Chem. 28 (11) (2011) 1367-1371.

编辑推荐 0

Metrics

阅读次数

全文

184

HTML			PDF

最新录用	在线预览	正式出版	最新录用	在线预览	正式出版
0	0	0	0	0	184

来源	本网站	其他网站

次数	50	134
比例	27%	73%

摘要

1118

最新录用	在线预览	正式出版

0	0	1118

来源	本网站	其他网站

次数	56	1062
比例	5%	95%

Modified molecular matrix model for predicting molecular composition of naphtha

Modified molecular matrix model for predicting molecular composition of naphtha

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐 0

Metrics

本文评价

[1]	Siyue Ren, Xiao Feng. Emergy evaluation of aromatics production from methanol and naphtha[J]. 中国化学工程学报, 2022, 46(6): 134-141.
[2]	Mohsen Rezaeimanesh, Ali Asghar Ghoreyshi, S.M. Peyghambarzadeh, Seyed Hassan Hashemabadi. A coupled CFD simulation approach for investigating the pyrolysis process in industrial naphtha thermal cracking furnaces[J]. 中国化学工程学报, 2022, 44(4): 528-542.
[3]	Chen Chen, Qiong Tang, Hong Xu, Lei Liu, Mingxing Tang, Xuekuan Li, Jinxiang Dong. Alkylation of naphthalene with n-butene catalyzed by liquid coordination complexes and its lubricating properties[J]. 中国化学工程学报, 2021, 39(11): 306-313.
[4]	Chong Peng, Zhiming Zhou, Xiangchen Fang, Hualin Wang. Thermodynamics and kinetics insights into naphthalene hydrogenation over a Ni-Mo catalyst[J]. 中国化学工程学报, 2021, 39(11): 173-182.
[5]	Xiaoping Su, Pu An, Junwen Gao, Rucheng Wang, Yujuan Zhang, Xi Li, Yangkun Zhao, Yongqi Liu, Xiaoxun Ma, Ming Sun. Selective catalytic hydrogenation of naphthalene to tetralin over a NiMo/Al₂O₃ catalyst[J]. 中国化学工程学报, 2020, 28(10): 2566-2576.
[6]	Wenpeng Li, Suohe Yang, Xiaoyan Guo, Guangxiang He, Haibo Jin. The effect of operating conditions on acylation of 2-methylnaphthalene in a microchannel reactor[J]. Chinese Journal of Chemical Engineering, 2018, 26(6): 1307-1311.
[7]	Feng Hua, Zhou Fang, Tong Qiu. Application of convolutional neural networks to large-scale naphtha pyrolysis kinetic modeling[J]. Chinese Journal of Chemical Engineering, 2018, 26(12): 2562-2572.
[8]	Hao Sun, Saijian Shi, Zhenggui Gu. Isomerization of alkyl naphthalene and refining of 2-methylnaphthalene[J]. , 2017, 25(2): 149-152.
[9]	Changhai Li, Dongmei Jia. Adsorption of 2-naphthalenesulfonic acid/sulfuric acid/sulfurous acid from aqueous solution by iron-impregnated weakly basic resin: Equilibrium and model[J]. Chinese Journal of Chemical Engineering, 2016, 24(11): 1522-1526.
[10]	赵亮, 郭新闻, 刘民, 王祥生, 宋春山. Methylation of 2-Methylnaphthalene with Methanol over NH₄F and Pt Modified HZSM-5 Catalysts[J]. , 2010, 18(5): 742-749.
[11]	田文玉, 薛为岚, 曾作祥, 邵记. Kinetics of 2-Methyl-6-acetyl-naphthalene Liquid Phase Catalytic Oxidation[J]. , 2009, 17(1): 72-77.
[12]	田正华, 王沛, 赵桂利. 异丙基萘的分子间烷基转移及其在制备2,6-二异丙基萘中的应用[J]. , 2007, 15(4): 606-610.
[13]	夏清, 马沛生. 2，6-萘二甲酸二甲酯在有机溶剂中溶解度的测定与关联[J]. , 2007, 15(2): 215-220.
[14]	邵记, 曾作祥, 薛为岚, 吴超. 甲基-酰基-萘在庚烷、辛烷和十二烷中溶解度的测定与关联[J]. , 2006, 14(6): 780-783.
[15]	朱群雄, 李澄非. 输入训练神经网络的维数约简算法及其在化工过程建模中的应用[J]. , 2006, 14(5): 597-603.