计算机模拟技术在生物质转化中的应用研究进展

doi:10.16085/j.issn.1000-6613.2019-1537

摘要/Abstract

摘要：

生物质是指源于动植物的、具有碳固定能力的可再生资源。本文综述了计算机模拟在生物质转化中的研究进展。首先介绍了生物质转化利用的主要技术，包括生物质气化、液化、物理转化、生物转化等。在此基础上，总结了利用计算机模拟技术辅助生物质转化研究的应用进展，包括基于热力学模型和动力学模型的流程模拟Aspen Plus、PRO/Ⅱ，以量子化学为基础的分子模拟Gaussian 09w、Materials Studio，对多个参数交互作用效果分析并优化的条件优化模拟Design Expert等。同时，概述了全生命周期评估（life cycle assessment，LCA）、神经网络模拟（artificial neural networks，ANNs）、数值模拟在生物质转化中的应用，最后对计算机模拟在生物质转化中的发展应用进行了展望，指出应继续研究贴合生物质转化过程，避免对真实过程简化的模型，同时进一步研究通过不同模拟的复合来增强模拟效果的可靠性。

关键词: 生物质, 流程模拟, 分子模拟, 条件优化模拟

Abstract:

Biomass is a renewable energy source that is derived from animals and plants and has carbon fixation capabilities. This paper reviews the research progress of computer simulation in biomass conversion. Firstly, the main conversion and utilization technologies of biomass are introduced, which includes biomass gasification, liquefaction, physical conversion, bioconversion, etc. On the basis, the application progress of computer simulation assisting biomass conversion research is summarized, including process simulation based on thermodynamic model and kinetic model Aspen Plus and PRO/Ⅱ, and the molecular simulation based on quantum chemistry Gaussian 09w and Materials Studio, and the condition optimization simulation based on the analysis of the interaction of multiple parameters and the optimization Design Expert. Meanwhile, the application of life cycle assessment (LCA), neural network simulation (artificial neural networks, ANNs), and numerical simulation in biomass conversion are overviewed. Finally, the future development of computer simulation in biomass conversion is prospected. It is pointed out that it should continue to study the process which conforms biomass conversion, avoiding the model of simplifying the real process, and further enhance the reliability of simulation effect through the combination of different simulations.

Key words: biomass, process simulation, molecular simulation, conditional optimization simulation

中图分类号:

S216.2

郭鹏坤, 李攀, 常春, 徐桂转, 石晓华, 白净, 方书起. 计算机模拟技术在生物质转化中的应用研究进展[J]. 化工进展, 2020, 39(8): 3027-3040.

Pengkun GUO, Pan LI, Chun CHANG, Guizhuan XU, Xiaohua SHI, Jing BAI, Shuqi FANG. Advances in the application of computer simulation technology in biomass conversion[J]. Chemical Industry and Engineering Progress, 2020, 39(8): 3027-3040.

参考文献

1	SHIN J D, XU C B, KIM S H, et al. Biomass conversion of plant residues[M]//Food Bioconversion. Amsterdam: Elsevier. 2017：351-383.
2	DUFOUR A. Thermochemical conversion of biomass for the production of energy and chemicals[M]. New Jersey: John Wiley & Sons, 2016:158-190.
3	VERMA M, GODBOUT S, BRAR S K, et al. Biofuels production from biomass by thermochemical conversion technologies[J]. International Journal of Chemical Engineering, 2012, 2012: 542426.
4	DAI J J, JEAN S, JOHN R, et al. Gasification of woody biomass[J]. Chem. Biomol., 2015, 6: 77-99.
5	IBARRA G P, RONG B. A review of the current state of biofuels production from lignocellulosic biomass using thermochemical conversion routes[J]. Chinese Journal of Chemical Engineering, 2018, 27(7): 1523-1535.
6	HOSSAIN M A, JEWARATNAM J, GANESAN P. Prospect of hydrogen production from oil palm biomass by thermochemical process-a review[J]. International Journal of Hydrogen Energy, 2016, 41(38): 16637-16655.
7	HOSSEINI S E, WAHID M A. Utilization of palm solid residue as a source of renewable and sustainable energy in Malaysia[J]. Renewable and Sustainable Energy Reviews, 2014, 40: 621-632.
8	ANTOLINI D, AIL S S, PATUZZI F, et al. Experimental investigations of air-CO₂biomass gasification in reversed downdraft gasifier[J]. Fuel, 2019, 253: 1473-1481.
9	LI Z, ZHU B, WANG B, et al. Stress responses to trichlorophenol in Arabidopsis and integrative analysis of alteration in transcriptional profiling from microarray[J]. Gene, 2015, 555(2): 159-168.
10	LIU H, YU L, YANG L, et al. Vasoplegic syndrome: an update on perioperative considerations[J]. Journal of Clinical Anesthesia, 2017, 40: 63-71.
11	ZEB H, CHOI J, KIM Y, et al. A new role of supercritical ethanol in macroalgae liquefaction (Saccharina japonica): understanding ethanol participation, yield, and energy efficiency[J]. Energy, 2017, 118: 116-126.
12	GEERTEN VAN DE K, KAMP L, REZAEI J. Selection of biomass thermochemical conversion technology in the Netherlands: a best worst method approach[J]. Journal of Cleaner Production, 2017, 166: 32-39.
13	MINH LOY A C, YUSUP S, CHIN B L FUI, et al. Comparative study of in-situ catalytic pyrolysis of rice husk for syngas production: kinetics modelling and product gas analysis[J]. Journal of Cleaner Production, 2018, 197: 1231-1243.
14	HU X, GHOLIZADEH M. Biomass pyrolysis: a review of the process development and challenges from initial researches up to the commercialisation stage[J]. Journal of Energy Chemistry, 2019, 39: 109-143.
15	DING Y, ZHANG J, HE Q, et al. The application and validity of various reaction kinetic models on woody biomass pyrolysis[J]. Energy, 2019, 179:784-791.
16	BRIDGWATER A V. Review of fast pyrolysis of biomass and product upgrading[J]. Biomass and Bioenergy, 2012, 38: 68-94.
17	BRAND S, SUSANTI R F, KIM S K, et al. Supercritical ethanol as an enhanced medium for lignocellulosic biomass liquefaction: influence of physical process parameters[J]. Energy, 2013, 59: 173-182.
18	DIMITRIADIS A, BEZERGIANNI S. Hydrothermal liquefaction of various biomass and waste feedstocks for biocrude production: a state of the art review[J]. Renewable and Sustainable Energy Reviews, 2017, 68: 113-125.
19	MA Y, WANG J, TAN W, et al. Directional liquefaction of lignocellulosic biomass for value added monosaccharides and aromatic compounds[J]. Industrial Crops and Products, 2019, 135: 251-259.
20	TABAKAEV R B, ASTAFEV A V, KAZAKOV A V, et al. Biomass conversion into solid composite fuel for bed-combustion[J]. MATEC Web of Conferences, 2015, 37: 1056.
21	YANG D, WEI S J, WEN Q M, et al. Comparison of pretreatments for lignocellulosic biomass[J]. Advanced Materials Research, 2014, 1008/1009: 111-115.
22	WEN H, WACHEMO A C, ZHANG L, et al. A novel strategy for efficient anaerobic co-digestion based on the pretreatment of corn stover with fresh vinegar residue[J]. Bioresource Technology, 2019, 288: 121412.
23	DENG C, LIN R, CHENG J, et al. Can acid pre-treatment enhance biohydrogen and biomethane production from grass silage in single-stage and two-stage fermentation processes?[J]. Energy Conversion and Management, 2019, 195: 738-747.
24	郭秀娟. 生物质选择性热裂解机理研究[D]. 杭州：浙江大学, 2011.
24	GUO X J. Mechanism research on the selective pyrolysis behavior of biomass[D].Hangzhou: Zhejiang University, 2011.
25	LI M, YANG S, SUN R. Recent advances in alcohol and organic acid fractionation of lignocellulosic biomass[J]. Bioresource Technology, 2016, 200: 971-980.
26	JEROEN S, EMMIE D, BOUCHRA B, et al. Biorefining of wheat straw using an acetic and formic acid based organosolv fractionation process[J]. Bioresource Technology, 2014, 156: 275-282.
27	闫桂焕，孙奉仲，孙荣峰，等. 生物质气化过程的热力学模型研究[J]. 农业机械学报, 2010, 41(9): 85-89.
27	YAN G H, SUN F Z, SUN R F, et al. Research on thermo dynamic model of biomass gasification process[J]. Transactions of the Chinese Society of Agricultural Machinery, 2010, 41(9): 85-89.
28	JARUNGTHAMMACHOTE S, DUTTA A. Equilibrium modeling of gasification: gibbs free energy minimization approach and its application to spouted bed and spout-fluid bed gasifiers[J]. Energy Conversion and Management, 2008, 49(6): 1345-1356.
29	PUIG-GAMERO M, ARGUDO-SANTAMARIA J, VALVERDE J L, et al. Three integrated process simulation using Aspen Plus?: pine gasification, syngas cleaning and methanol synthesis[J]. Energy Conversion and Management, 2018, 177: 416-427.
30	YU J, SMITH J D. Validation and application of a kinetic model for biomass gasification simulation and optimization in updraft gasifiers[J]. Chemical Engineering and Processing-Process Intensification, 2018, 125: 214-226.
31	SADHWANI N, LI P C, EDEN M, et al. Process modeling of fluidized bed biomass-CO₂ gasification using ASPEN plus[J].Computer Aided Chemical Engineering, 2017, 40: 2509-2514.
32	PARDO-PLANAS O, ATIYEH H K, PHILLIPS J R, et al. Process simulation of ethanol production from biomass gasification and syngas fermentation[J]. Bioresource Technology, 2017, 245: 925-932.
33	HE J, ZHANG W. Techno-economic evaluation of thermo-chemical biomass-to-ethanol[J]. Applied Energy, 2011, 88(4): 1224-1232.
34	PALA L P R, WANG Q, KOLB G, et al. Steam gasification of biomass with subsequent syngas adjustment using shift reaction for syngas production: an Aspen Plus model[J]. Renewable Energy, 2017, 101: 484-492.
35	RAVIKIRAN A, RENGANATHAN T, PUSHPAVANAM S, et al. Generalized analysis of gasifier performance using equilibrium modeling[J]. Industrial & Engineering Chemistry Research, 2011, 51(4): 1601-1611.
36	KAUSHAL P, TYAGI R. Advanced simulation of biomass gasification in a fluidized bed reactor using ASPEN PLUS[J]. Renewable Energy, 2017, 101: 629-636.
37	PETERS J F, BANKS S W, BRIDGWATER A V, et al. A kinetic reaction model for biomass pyrolysis processes in Aspen Plus[J]. Applied Energy, 2017, 188: 595-603.
38	KRISTIN O, YRJ? S, JANI L. Process simulation development of fast pyrolysis of wood using Aspen Plus[J]. Energy & Fuels, 2015, 29(1): 205-217.
39	WRIGHT M M, DAUGAARD D E, SATRIO J A, et al. Techno-economic analysis of biomass fast pyrolysis to transportation fuels[J]. Fuel, 2010, 89: S2-S10.
40	HUMBIRD D, TRENDEWICZ A, BRAUN R, et al. One-dimensional biomass fast pyrolysis model with reaction kinetics integrated in an Aspen Plus biorefinery process model[J]. ACS Sustainable Chemistry & Engineering, 2017, 5(3): 2463-2470.
41	乔庆安，张建，鲍杰. 产业化工况下木质纤维素生物炼制过程的流程模拟[J]. 华东理工大学学报（自然科学版）, 2013, 39(4): 427-432.
41	QIAO Q A, ZHANG J, BAO J. Flowsheet simulation of industrial scale biorefining processes of lignocellulose[J].Journal of East China University of Science and Technology(Natural Science Edition), 2013, 39(4): 427-432.
42	DAMARTZIS T, MICHAILOS S, ZABANIOTOU A. Energetic assessment of a combined heat and power integrated biomass gasification-internal combustion engine system by using Aspen Plus?[J]. Fuel Processing Technology, 2012, 95: 37-44.
43	SADHUKHAN J, ZHAO Y, SHAH N, et al. Performance analysis of integrated biomass gasification fuel cell (BGFC) and biomass gasification combined cycle (BGCC) systems[J]. Chemical Engineering Science, 2010, 65(6): 1942-1954.
44	欧凤林. 褐煤与生物质在CO₂气氛下共气化过程特性的研究[D]. 长沙：长沙理工大学, 2015.
44	OU F L. The study on co-gasification process characteristics of lignite with biomass in the CO₂ atmosphere[D]. Changsha：Changsha University of Science & Technology, 2015.
45	郝巧铃.生物质与煤共气化特性的研究[D]. 太原：太原理工大学，2012.
45	HAO Q L. Co-gasification characteristic of biomass and coal[D].Taiyuan: Taiyuan University of Technology，2012.
46	ANNA L P, MARK A S, AKWASI A B.Utilization of eucalyptus for electricity production in Brazil via fast pyrolysis: a techno-economic analysis[J]. Renewable Energy, 2018, 119: 590-597.
47	黄金保. 纤维素快速热解机理的分子模拟研究[D].重庆：重庆大学, 2010.
47	HUANG J B. Molecular simulation study of pyrolysis mechanism of cellulose[D].Chongqing: Chongqing University, 2010.
48	李明明. 量子化学软件在大学无机化学教学中的应用[J]. 科教文汇(中旬刊), 2019(6): 70-71.
48	LI M M. Application of quantum chemistry software in the teaching of inorganic chemistry in universities[J]. The Science Education Article Collects, 2019(6): 70-71.
49	WEIJING D, WEIHONG Z, XIAODONG Z, et al. The application of DFT in catalysis and adsorption reaction system[J]. Energy Procedia, 2018, 152: 997-1002.
50	MU B, XU H, LI W, et al. Quantitation of fast hydrolysis of cellulose catalyzed by its substituents for potential biomass conversion[J]. Bioresource Technology, 2019, 273: 305-312.
51	ZHANG M, GENG Z, YU Y. Density functional theory (DFT) study on the dehydration of cellulose[J]. Energy & Fuels, 2011, 25(6): 2664-2670.
52	ZHOU B, DICHIARA A, ZHANG Y, et al. Tar formation and evolution during biomass gasification: an experimental and theoretical study[J]. Fuel, 2018, 234: 944-953.
53	LU Q, TIAN H, HU B, et al. Pyrolysis mechanism of holocellulose-based monosaccharides: the formation of hydroxyacetaldehyde[J]. Journal of Analytical and Applied Pyrolysis, 2016, 120: 15-26.
54	黄金保, 刘朝, 魏顺安,等. 纤维素热解形成左旋葡聚糖机理的理论研究[J].燃料化学学报, 2011,39(8):590-594.
54	HUANG J B, LIU Z, WEI S A, et al. A theoretical study on the mechanism of levoglucosan formation in cellulose pyrolysis[J]. Journal of Fuel Chemistry and Technology, 2011,39(8):590-594.
55	LI J, YANG Y, ZHANG D. DFT study of fructose dehydration to 5-hydroxymethylfurfural catalyzed by imidazolium-based ionic liquid[J]. Chemical Physics Letters, 2019, 723: 175-181.
56	HUANG J, LIU C, WEI S, et al. Density functional theory studies on pyrolysis mechanism of β-D-glucopyranose[J]. Journal of Molecular Structure: THEOCHEM, 2010, 958(1-3): 64-70.
57	梁洪林. 纤维素热解释放小分子气体机理的量子化学研究[D]. 吉林：东北电力大学，2019.
57	LIANG H L. Quantum chemical study on the mechanism of release of small molecular gases by pyrolysis of cellulose[D]. Jilin: Northeast Electric Power University, 2019.
58	王鹏恒. CO/H₂ /CH₄在催化剂 Pd/γ-Al₂O₃上吸附机理的密度泛函研究[D]. 武汉：华中科技大学，2014.
58	WANG P H. Density functional theory study of adsorption mechanism of gasified biomass over catalyst Pd/γ-Al₂O₃[D]. Wuhan: Huazhong University of Science and Technology, 2014.
59	GIUPPONI G, HARVEY M J, DE FABRITIIS G. The impact of accelerator processors for high-throughput molecular modeling and simulation[J]. Drug Discovery Today, 2008, 13(23-24): 1052-1058.
60	PRONK S, PáLL S, SCHULZ R, et al. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit[J]. Bioinformatics, 2013, 29(7): 845-854.
61	VASUDEVAN V, MUSHRIF S H. Insights into the solvation of glucose in water, dimethyl sulfoxide (DMSO), tetrahydrofuran (THF) and N,N-dimethylformamide (DMF) and its possible implications on the conversion of glucose to platform chemicals[J]. RSC Advances, 2015, 5(27): 20756-20763.
62	朱有涛. 离子液体溶解和降解木质素机理的理论研究[D].济南: 山东大学, 2017.
62	ZHU Y T. Theoretical studies on dissolution and depolymerization mechanisms of lignin in ionic liquid[D].Jinan: Shandong University, 2017.
63	李垚. 离子液体溶解生物质的分子模拟研究[D]. 北京：中国科学院大学（中国科学院过程工程研究所）, 2017.
63	LI Y. Molecular simulation study on dissolution of lignocellulosic biomass in ionic liquids[D]. Beijing:University of Chinese Academy of Sciences(Institute of Process Engineering, Chinese Academy of Sciences), 2017.
64	ISA K M, DAUD S, HAMIDIN N, et al. Thermogravimetric analysis and the optimisation of bio-oil yield from fixed-bed pyrolysis of rice husk using response surface methodology (RSM)[J]. Industrial Crops and Products, 2011, 33(2): 481-487.
65	CHANG C, DENG L, XU G Z. Efficient conversion of wheat straw into methyl levulinate catalyzed by cheap metal sulfate in a biorefinery concept[J]. Industrial Crops and Products, 2018, 117: 197-204.
66	樊永胜. 生物质真空热解及催化转化制备生物油的基础研究[D]. 镇江: 江苏大学, 2016.
66	FAN Y S. Basic study on vacuum pyrolysis and catalytic transformation of biomass for preparation of bio-oil[D]. Zhenjiang: Jiangsu University, 2016.
67	TIONG Y W, YAP C L, GAN S, et al. Optimisation studies on the conversion of oil palm biomass to levulinic acid and ethyl levulinate via indium trichloride-ionic liquids: a response surface methodology approach[J]. Industrial Crops and Products, 2019, 128: 221-234.
68	伊乐其. 生物质对中低阶煤热解行为的影响及其BP神经网络模型[D]. 上海: 华东理工大学, 2015.
68	YI L Q. The influence of biomass addition on low rank coal pyrolysis behavior and its BP neural network model[D].Shanghai：East China University of Science and Technology, 2015.
69	GHUGARE S B, TIWARY S, ELANGOVAN V, et al. Prediction of higher heating value of solid biomass fuels using artificial intelligence formalisms[J]. BioEnergy Research, 2014, 7(2): 681-692.
70	GHUGARE S B, TAMBE S S. Genetic programming based high performing correlations for prediction of higher heating value of coals of different ranks and from diverse geographies[J]. Journal of the Energy Institute, 2017, 90(3): 476-484.
71	GARCíA R, PIZARRO C, LAVíN A G, et al. Spanish biofuels heating value estimation. part II: Proximate analysis data[J]. Fuel, 2014, 117: 1139-1147.
72	ALEX O B F, ALLAN K D B, SOFIANE L,et al. Application of artificial neural networks to predict viscosity, iodine value and induction period of biodiesel focused on the study of oxidative stability[J]. Fuel, 2015, 145: 127-135.
73	ISMAIL F, SELEN C.Process synthesis of biodiesel production plant using artificial neural networks as the surrogate models[J]. Computers & Chemical Engineering, 2012, 46: 105-123.
74	王红彦. 基于LCA的秸秆沼气和秸秆热解气化工程环境影响评价[D]. 北京：中国农业科学院, 2018.
74	WANG H Y. Environmental impact evaluation of straw biogas and straw gasification projects based on LCA[D].Beijing：Chinese Academy of Agricultural Sciences, 2018.
75	YANG K, ZHU N, YUAN T. Analysis of optimum scale of biomass gasification combined cooling heating and power (CCHP) system based on life cycle assessment(LCA)[J]. Procedia Engineering, 2017, 205: 145-152.
76	SOAM S, BORJESSON P, SHARMA P K, et al. Life cycle assessment of rice straw utilization practices in India[J]. Bioresource Technology, 2017, 228: 89-98.
77	SHI X, RONSSE F, ROEGIERS J, et al. 3D Eulerian-eulerian modeling of a screw reactor for biomass thermochemical conversion. part 1: Solids flow dynamics and back-mixing[J]. Renewable Energy, 2019, 143: 1465-1476.
78	HARISWARAN S, NICHOLAS D, JAMES J L,et al. Coupled CFD and chemical-kinetics simulations of cellulosic-biomass enzymatic hydrolysis: mathematical-model development and validation[J]. Chemical Engineering Science, 2019, 206: 348-360.

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