Algebraic analysis modeling method for complex reactions

doi:10.11949/j.issn.0438-1157.20171224

Abstract

Abstract:

In chemical production design, reactors are usually designed only based on experimental data and practical experience, especially in the case of complicated chemical reaction. Due to the absence of an effective model that simulates and predicts the behavior of the reaction systems, the systems are often not operated under optimal conditions, resulting in an increase in costs or a decrease in desired reaction product. Therefore, a model is needed to optimize the system. Starting from atomic scope, this paper will use an algebraic analysis modeling method to explore the relation among components in complicated chemical reaction, seek all possible reaction steps, and establish plausible reaction network. Specifically, the reaction model will be developed using Aspen, and the best approximation that describes the complicated chemical reaction will be analyzed and chosen. In conjunction with the model and its implication, it will allow optimization of the design and even control over the direction of the reaction. In this paper, coal gasification reaction will be optimized by this method.

Key words: reaction network, model, reaction, simulation, coal gasification

摘要：

反应器的设计通常只能以实验室实验数据或者经验规则作为标准，特别是对于复杂的化学反应。由于缺少一个合适的模型进行模拟、预测，很难确定该反应系统的最优条件，导致生产成本增高或者理想产物产量降低。为实现反应系统的优化，需要建立一个能够准确模拟、预测反应系统的模型。介绍了一种确定可行反应网络的代数分析建模方法，从原子层面出发探究复杂反应中所涉及的物质之间的关系，基于原子矩阵的转换寻找所有可行的反应步骤，建立可行的反应网络。通过Aspen Plus建立反应模型，模拟分析选择最适合的复杂反应系统的模型。分析结果与模型指导下的实验相结合，可达到对复杂反应系统进行优化设计、模拟预测乃至控制反应进行方向的目的。根据该建模方法对煤汽化反应系统进行了优化。

关键词: 反应网络, 模型, 反应, 模拟, 煤气化

CLC Number:

TQ018

ZHOU Leihao, LIU Guilian. Algebraic analysis modeling method for complex reactions[J]. CIESC Journal, 2018, 69(3): 1030-1037.

周雷皓, 刘桂莲. 复杂反应的代数分析建模方法[J]. 化工学报, 2018, 69(3): 1030-1037.

References 30

[1]	MOGGRIDGE G D, CUSSLER E L. Chemical Product Design[M]. London:Cambridge University Press, 2001
[2]	NISHIDA N, STEPHANOPOULOS G, WESTERBERG A W. A review of process synthesis[J]. AIChE J., 1981, 27(3):321-351.
[3]	COREY E J, HOWE W J, PENSAK D A. Computer-assisted synthetic analysis-methods for machine generation of synthetic intermediates involving multi-step look ahead[J]. Chemischer Informationsdienst, 1974, 6(8):7724-7737.
[4]	PARENTY A D C, BUTTON W G, OTT M A. An expert system to predict the forced degradation of organic molecules[J]. Mol. Pharm., 2013, 10(8):2962-2974.
[5]	UGI I K, BAUMGARTNER R, FONTAIN E, et al. Computer programs for the solution of chemical problems by molecular logic[J]. Pure Appl. Chem., 1988, 60(11):1573-1586.
[6]	UGI I K, GILLESPIE P. Chemistry and logic structure(Ⅲ):Representation of chemical systems and interconversion by BE matrices and their transformation properties[J]. Angew. Chem. Int. Ed., 1971, 10(12):914-915.
[7]	WANG L P, TITOV A, MCGIBBON R, et al. Discovering chemistry with an ab initio nanoreactor[J]. Nat. Chem., 2014, 6(12):1044-1048.
[8]	ARIS R, MAH R H S. Independence of chemical reactions[J]. Reaction Kinetics & Catalysis Letters, 1987, 33(1):9-15.
[9]	BONVIN D, RIPPIN D W T. Target factor analysis for the identification of stoichiometric models[J]. Chem. Eng. Sci., 1990, 45(12):2417-2426.
[10]	BHATT N, KERIMOGLU N, AMRHEIN M, et al. Incremental identification of reaction systems-a comparison between rate-based and extent-based approaches[J]. Chem. Eng. Sci., 2012, 83(49):24-38.
[11]	BURNHAM S C, SEARSON D P, WILLIS M J, et al. Inference of chemical reaction networks[J]. Chem. Eng Sci., 2008, 63(4):862-873.
[12]	FRANCESCHINI G, MACCHIETTO S. Novel anticorrelation criteria for design of experiments:algorithm and application[J]. AIChE J., 2008, 54(12):3221-3238.
[13]	GALVANIN F, BAROLO M, BEZZO F, et al. A back off strategy for model-based experiment design under parametric uncertainty[J]. AIChE J., 2010, 56(8):2088-2102.
[14]	LUNA M, MARTINEZ E A. Bayesian approach to run-to-run optimization of animal cell bioreactors using probabilistic tendency models[J]. Ind. Eng. Chem. Res., 2014, 53(44):17252-17266.
[15]	ZHANG W. Model building methodology for complex reaction systems[D]. Manchester:University of Manchester Institute of Science and Technology, 2004.
[16]	ZHANG W, MICHAEL B, CONSTANTIONS T, et al. Model building methodology for complex reaction systems[J]. Ind. Eng. Chem. Res., 2015, 54(16):4603-4615
[17]	ZIMMERMAN P M. Automated discovery of chemically reasonable elementary reaction steps[J]. J. Comput. Chem., 2013, 34(16):1385.
[18]	HOLIASTOS K, MANOUSIOUTHAKIS V. Automatic synthesis of thermodynamically feasible reaction clusters[J]. AIChE J., 1998, 44(1):164-173.
[19]	BINNS M, THEODOROPOULOS C. An integrated knowledge-based approach for modeling biochemical reaction networks[J]. Comput. Chem.Eng., 2011, 35(12):3025-3043.
[20]	张斌, 李政, 江宁, 等. 基于Aspen Plus建立气流床煤气化炉模型[J]. 化工学报, 2003, 54(8):1179-1182. ZHANG B, LI Z, JIANG N, et al. Modeling of entrained bed coal gasifiers with Aspen Plus[J]. Journal of Chemical Industry and Engineering(China), 2003, 54(8):1179-1182.
[21]	欧阳朝斌, 段东平, 郭占成, 等. 天然气-煤共气化制备合成气热态模拟[J]. 化工学报, 2005, 56(10):1936-1941. OUYANG Z B, DUAN D P, GUO Z C, et al. Natural gas &coal co-gasification to produce synthesis gas in hot simulation[J]. Journal of Chemical Industry and Engineering(China), 2005, 56(10):1936-1941.
[22]	陈新明, 史绍平, 闫姝, 等. 燃烧前CO2 捕集技术在IGCC发电中的应用[J]. 化工学报, 2014, 65(8):3193-3201. CHEN X M, SHI S P, YAN S, et al. Application of CO2 capture technology before burning in IGCC power generation system[J]. CIESC Journal, 2014, 65(8):3193-3201.
[23]	孙付成, 任强强, 王昕, 等. 循环流化床煤气化细粉灰硫氮转化分析[J]. 锅炉技术, 2015, 46(1):33-44. SUN F C, REN Q Q, WANG X, et al. Circulating fluidized bed coal gasification thin blues sulfur nitrogen transformation analysis[J]. Boiler Technology, 2015, 46(1):33-44.
[24]	徐惠彦. 库伦法测定煤中全硫的影响因素及措施[J]. 经济技术协作信息, 2016, (3):88. XU H Y. Determination the influence factors of total sulfur in coal by coulomb method and measures[J]. Economic and Technological Cooperation Information, 2016, (3):88.
[25]	张婷, 郭庆华, 梁钦锋, 等. 煤气化过程中含硫化合物生成特性的热力学研究[J]. 中国电机工程学报, 2011, 31(11):32-38. ZHANG T, GUO Q H, LIANG Q F, et al. The generation properties of sulfur compounds during coal gasification by thermodynamic equilibrium simulation[J]. Proceedings of the CSEE, 2011, 31(11):32-38.
[26]	徐有宁, 张忠东, 李静海, 等. 抑制氮氧化物无烟燃煤炉内煤气化过程[J]. 化工学报, 2000, 51(S1):122-125. XU Y N, ZHANG Z D, LI J H, et al. Inhibition of nitrogen oxide smokeless coal coal gasification process in the furnace[J]. Journal of Chemical Industry and Engineering(China), 2000, 51(S1):122-125.
[27]	陈玉, 张福丽, 姚辉超. 催化水煤气变化反应的计算模拟进展[J].化工进展, 2012, 31(10):2221-2227. CHEN Y, ZHANG F L, YAO H C. The computational simulation progress of catalytic water gas change reaction[J]. Chem. Ind. Eng. Prog., 2012, 31(10):2221-2227.
[28]	KI H K, 付国伟, 杜国萍. 水煤气转换反应中氢的重整过程分析[J]. 现代冶金, 2015, (1):75-76. KI H K, FU G W, DU G P. The analysis of reforming process about hydrogen in the water gas conversion reaction[J]. Modern Metallurgy, 2015, (1):75-76.
[29]	潘婵婵, 刘霞, 霍威, 等. 煤气化细灰及其原煤的热解特性与官能团特征[J]. 化工学报, 2015, 66(4):1449-1458. PAN C C, LIU X, HUO W, et al. Functional groups and pyrolysis characteristics of fine gasification ashes and raw coals[J]. CIESC Journal, 2015, 66(4):1449-1458.
[30]	黎军. 德士古水煤浆加压气化技术[R]. 淮南化工, 2012. LI J. Texaco coal-water slurry pressurized gasification technology[R]. Huainan Chemical, 2012.