КОРОТКОЦИКЛОВАЯ БЕЗНАГРЕВНАЯ АДСОРБЦИЯ ДЛЯ ИЗВЛЕЧЕНИЯ ВОДОРОДА, КИСЛОРОДА И АЗОТА ИЗ ГАЗОВЫХ СМЕСЕЙ: МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ, ОПТИМИЗАЦИЯ РЕЖИМОВ ФУНКЦИОНИРОВАНИЯ И ПРОЕКТИРОВАНИЕ УСТАНОВОК
Аннотация
Анализ и обобщение мирового опыта в области решения задач математического моделирования, оптимизации режимов функционирования и проектирования технологических процессов разделения газовых смесей и извлечения ценных газов по способу короткоцикловой безнагревной адсорбции позволили вскрыть противоречия и сформулировать ряд проблем, связанных с дальнейшим развитием и интенсификацией циклических адсорбционных процессов, совершенствованием их аппаратурно-технологического оформления, методологии создания и исследования установок короткоцикловой безнагревной адсорбции. В настоящее время разработаны: 1) метод математического моделирования динамики технологического процесса разделения газовых смесей и извлечения продуктовых газов (водорода, кислорода, азота и др.), отличающийся учетом влияния процессов массо- и теплопереноса в газовой и твердой фазах на кинетику диффузионного переноса адсорбтива (водорода, диоксида и оксида углерода, кислорода, азота) в пределах единичного адсорбера, возмущающих воздействий (состава, температуры и давления исходной газовой смеси (синтез-газа, атмосферного воздуха) и увязкой между собой моделей всех аппаратов и устройств, входящих в состав установки короткоцикловой безнагревной адсорбции; 2) процедура построения математической модели процесса разделения многокомпонентной газовой смеси и извлечения продуктового газа с использованием формулы аналитического метода, состоящей из следующих пяти этапов: получение структуры математической модели; получение экспериментальных данных об исследуемомом технологическом процессе/объекте в лабораторных условиях; определение вектора параметров приближенной математической модели; анализ адекватности построенной математической модели; обеспечение адекватности математической модели; 3) методы решения уравнений математической модели процесса короткоцикловой безнагревной адсорбции, позволяющие получать устойчивые конечно-разностные схемы и исключать возникновение возмущений (осцилляций) из-за наличия «крутых» адсорбционных фронтов и нелинейности модели; 4) подходы к решению задач оптимизации режимов функционироания и проектирования установок короткоцикловой безнагревной адсорбции: Blackbox Optimization и Simultaneous Tailored Optimization, сочетающие высокоэффективные методы оптимизации (последовательного квадратичного программирования, ветвей и границ и др.) и солверы пакетов прикладных программ MatLab и gPROMS. В статье проводится анализ и систематизация построения моделей и методов математического моделирования циклических адсорбционных процессов, постановок задач оптимизации режимов и проектирования для извлечения водорода, кислорода и азота из газовых смесей; математического, алгоритмического и информационного обеспечения для проектирования экономичных "конструкций" циклических установок адсорбционного разделения многокомпонентных газовых смесей. Дается сравнительная оценка эффективности и целесообразности предлагаемых подходов и методов к их решению, оценивается перспективность направлений дальнейшего развития процессов разделения и очистки газовых смесей по способу короткоцикловой безнагревной адсорбции с использованием современных средств и методов процессов и аппаратов химической технологии, системного анализа, математического моделирования и теории оптимизации (гибкости), которые наряду с интенсивно развивающимися средствами вычислительной техники позволяют создавать работоспособные энерго- и ресурсосберегающие химико-технологические процессы и установки в условиях неопределенности исходных данных.
Литература
Ackley M.W. Medical oxygen concentrators: a review of progress in air separation technology. Adsorption. 2019. V. 25. N 8. P. 1437–1474. DOI: 10.1007/s10450-019-00155-w.
Li H., Liao Z., Sun J. Modelling and simulation of twobed PSA process for separating H2 from methane steam reforming. Chin. J. Chem. Eng. 2019. V. 27. N 8. P. 1870–1878. DOI: 10.1016/ j.cjche.2018.11.022.
Shi W.-R., Tian C.-X., Ding Z.-Y. Review on Simulation, Optimization and Control of Pressure Swing Adsorption. Gaoxiao Huaxue Gongcheng Xuebao. 2018. V. 32. N 1. P. 8–15. DOI: 10.3969/j.issn.1003-9015.2018.01.002.
Ruthven D.M., Farooq S., Knaebel K.S. Pressure swing adsorption. New York: VCH. 1993. 189 p.
Marcinek A., Guderian J., Bathen D. Performance determination of high-purity N2-PSA-plants. Adsorption. 2020. V. 26. N 7. P. 1215-1226. DOI: 10.1007/s10450-020-00204-9.
Ding Z., Han Z., Fu Q. Optimization and analysis of the VPSA process for industrial-scale oxygen production. Ad-sorption. 2018. V. 24. N 5. P. 499-516. DOI: 10.1007/s10450-018-9956-z.
Li C., Xiao J., Pierre B. Optimization of Hydrogen Purification Performance of Layered Bed Pressure Swing Adsorption. Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban) / J. Wuhan Univ. of Technol (Transport. Sci. and Eng). 2020. V. 44. N 4. P. 753-759. DOI: 10.3963/j.issn.2095-3844.2020.04.032.
Ferreira D., Bárcia P., Whitley R.D. Single-Stage Vacuum Pressure Swing Adsorption for Producing High-Purity Oxygen from Air. Ind. Eng. Chem. Res. 2015. V. 54. N 39. P. 9591-9604. DOI: 10.1021/acs.iecr.5b02151.
Zhu X., Liu Y., Yang X. Study of a novel rapid vacuum pressure swing adsorption process with intermediate gas pressurization for producing oxygen. Adsorption. 2017. V. 23. N 1. P. 175-184. DOI: 10.1007/s10450-016-9843-4.
Liu B., Yu X., Shi W., Shen Y. Twostage VSA/PSA for capturing carbon dioxide (CO2) and producing hydrogen (H2) from steam-methane reforming gas. Int. J. Hydrogen Energy. 2020. V. 45. N 46. P. 24870-24882. DOI: 10.1016/j.ijhydene.2020.06.264.
Cruz P., Magalhaes F., Mendes A. On the optimization of cyclic adsorption separation processes. AIChE J. 2005. V. 51. N 5. P. 1377–1395. DOI: 10.1002/aic.10400.
Jiang L., Biegler L., Fox V. Simulation and Optimization of Pressure-Swing Adsorption Systems for Air Separation. AIChE J. 2003. V. 49. N 5. P. 1140–1157. DOI: 10.1002/aic.690490508.
Akulinin E.I., Golubyatnikov O.O., Dvoretsky D.S. Numerical study of cyclic adsorption processes of air oxygen enrichment in dynamics. J. Phys.: Conf. Ser. 2019. P. 012005. DOI: 10.1088/1742-6596/1278/1/012005.
Asgari M., Anisi H., Mohammadi H. Designing a commercial scale pressure swing adsorber for hydrogen purification. Pet. Coal. 2014. V. 56. N 5. P. 552-561.
Rao V.R., Farooq S., Krantz W.B. Design of a two-step pulsed pressure-swing adsorption-based oxygen concentrator. AIChE J. 2010. V. 56. N 2. P. 354-370. DOI: 10.1002/aic.11953.
Urich M.D., Vemula R.R., Kothare M.V. Multivariable model predictive control of a novel rapid pressure swing adsorption system. AIChE J. 2018. V. 64. N 4. P. 1234-1245. DOI: 10.1002/aic.16011.
Kopaygorodsky E.M., Guliants V.V., Krantz W.B. Predictive Dynamic Model of Single-Stage Ultra-Rapid Pres-sure Swing Adsorption. AIChE J. 2004. V. 50. N 5. P. 953–962. DOI: 10.1002/aic.10093.
Santos J.C., Portugal A.F., Magalhaes F.D. Simulation and optimization of small oxygen pressure swing adsorption units. Ind. Eng. Chem. Res. 2004. V. 43. P. 8328-8338. DOI: 10.1021/ie049701.
Cruz P., Santos J.C., Magalhaes F.D. Cyclic adsorption separation processes: analysis strategy and optimization procedure. Chem. Eng. Sci. 2003. V. 58. P. 3143–3158. DOI: 10.1016/S0009-2509(03)00189-1.
Makarem M.A., Mofarahi M., Jafarian B. Simulation and analysis of vacuum pressure swing adsorption using the differential quadrature method. Comp. Chem. Eng. 2019. V. 121. P. 483–496. DOI: 10.1016/j.compchemeng.2018.11.017.
Beeyani A.K., Singh K., Vyas R.K. Parametric studies and simulation of PSA process for oxygen production from air. Polish J. Chem. Tech. 2010.V. 12. N 2. P. 18-28. DOI: 10.2478/v10026-010-0013-2.
Sankararao B., Gupta S.K. Multiobjective optimization of pressure swing adsorbers for air separation. Ind. Eng. Chem. Res. 2007. V. 46. N 11. P. 3751-3765. DOI: 10.1021/ie0615180.
Ogawa K., Inagaki Y., Ohno A. Numerical analysis of O2 concentration, gaszeolite temperatures in two zeolite columns for an oxygen concentrator. Int. J. Heat Mass Transfer. 2019. V. 129. P. 238–254. DOI: 10.1016/j.ijheatmasstransfer.2018.09.052.
Santos J.C., Cruz P., Regala T. High-purity oxygen production by pressure swing adsorption. Ind. Eng. Chem. Res. 2007. V. 46. P. 591–599. DOI: 10.1021/ie060400g.
Hosseinzadeh Hejazi S., Rajendran A., Sawada J. Dy-namic Column Breakthrough and Process Studies of High-Purity Oxygen Production Using Silver-Exchanged Titano-silicates. Ind. Eng. Chem. Res. 2016. V. 55. N 20. P. 5993–6005. DOI: 10.1021/acs.iecr.6b01560.
Hosseinzadeh Hejazi S., Perez L.E., Rajendran A. Cycle Development and Process Optimization of High-purity Oxygen Production using Silver-Exchanged Titanosilicates (Ag-ETS-10). Ind. Eng. Chem. Res. 2017. V. 56. N 19. P. 5679–5691. DOI: 10.1021/acs.iecr.7b00219.
Xu M., Wu H.C., Lin Y.S. Simulation and optimization of pressure swing adsorption process for high-temperature air separation by perovskite sorbents. Chem. Eng. J. 2018. V. 354. P. 62–74. DOI: 10.1016/j.cej.2018.07.080.
Agarwal A., Biegler L., Zitney S. Superstructure-based optimal synthesis of pressure swing adsorption cycles for precombustion CO2 Capture. Ind. Eng. Chem. Res. 2010. V. 49. N 11. P. 5066–5079. DOI: 1021/ie900873j.
Dowling A., Vetukuri S., Biegler L. Large-scale optimization strategies for pressure swing adsorption cycle synthesis. AIChE J. 2012. V. 58. N 12. P. 3777–3791. DOI: 10.1002/aic.13928.
Huang Q., Malekian A., Eic M. Optimization of PSA process for producing enriched hydrogen from plasma re-actor gas. Sep. Purif. Tech. 2008. V. 62. N 1. P. 22–31. DOI: 10.1016/j.seppur.2007.12.017.
Tao W., Ma S., Xiao J. Simulation and optimization for hydrogen purification performance of vacuum pressure swing adsorption. Energy Proc. 2019. V. 158. P. 1917-1923. DOI: 10.1016/j.egypro.2019.01.441.
Asgari M. Synergistic material and process development: Application of a metalorganic framework, Cu-TDPAT, in single-cycle hydrogen purification and CO2 capture from synthesis gas. Chem. Eng. J. 2021. V. 414. P. 128778. DOI: 10.1016/j.cej.2021.128778.
Silva B., Solomon I., Ribeiro A.M. H-2 purification by pressure swing adsorption using CuBTC. Sep. Purif. Tech. 2013. V. 118. P. 744–756. DOI: 10.1016/j.seppur.2013.08.024.
Papadias D., Lee S., Ahmed S. Facilitating analysis of trace impurities in hydrogen: Enrichment based on the principles of pressure swing adsorption. Int. J. Hydrogen Energy. 2012. V. 37. N 19. P. 14413–14423. DOI: 10.1016/j.ijhydene.2012.07.057.
Yavary M., Ebrahim H.A., Falamaki C. The effect of number of pressure equalization steps on the performance of pressure swing adsorption process. Chem. Eng. Process. 2015. V. 87. P. 35-44. DOI: 10.1016/j.cep.2014.11.003.
Xiao J., Li C., Fang L. Machine learning–based optimization for hydrogen purification performance of layered bed pressure swing adsorption. Int. J. Energy Res. 2020. V. 44. N 6. P. 4475-4492. DOI: 10.1002/er.5225.
Delgado J.A., Águeda V.I., Uguina M.A. Adsorption and diffusion of H2, CO, CH4, and CO2 in BPL activated carbon and 13X zeolite: Evaluation of performance in pressure swing adsorption hydrogen purification by simulation. Ind. Eng. Chem. Res. 2014. V. 53. N 40. P. 15414-15426. DOI: 10.1021/ie403744u.
Abdeljaoued A., Relvas F., Mendes A. Simulation and experimental results of a PSA process for production of hydrogen used in fuel cells. J. Environ. Chem. Eng. 2018. V. 6. N 1. P. 338–355. DOI: 10.1016/j.jece.2017.12.010.
Ur Rehman A., Maosheng Z., Hayat A. Water sorption studies on ZnSO4-zeolite composite as potential thermochemical heat storage materials. Int. J. Energy Res. 2020. V. 44. N 1. P. 269-281. DOI: 10.1002/er.4910.
Aldrich J.H., Rousselo S.M., Yang M.L. Adsorptive Separation of Methane from Carbon Dioxide by Zeolite@ZIF Composite. Energy Fuels. 2019. V. 33. N 1. P. 348-355. DOI: 10.1021/acs.energyfuels.8b03484.
Lehmann C., Kolditz O., Nagel T. Modelling sorption equilibria and kinetics in numerical simulations of dynamic sorption experiments in packed beds of salt/zeolite composites for thermochemical energy storage. Int. J. Heat Mass Transfer. 2019. V. 128. P. 1102-1113. DOI: 10.1016/j.ijheatmasstransfer.2018.09.042.
Sharma I., Friedrich D., Golden T. Monolithic Adsorbent-Based Rapid-Cycle Vacuum Pressure Swing Adsorp-tion Process for Carbon Capture from Small-Scale Steam Methane Reforming. Ind. Eng. Chem. Res. 2020. V. 59. N 15. P. 7109-7120. DOI: 10.1021/acs.iecr.9b05337.
Ostrovsky G.M., Ziyatdinov N.N., Lapteva T.V. Optimization of Chemical Process with Joint Chance Constraints. Ind. Eng. Chem. Res. 2017. V. 56. N 12. P. 3309–3331. DOI: 10.1021/acs.iecr.6b02683.
Ostrovsky G.M., Lapteva T.V., Ziyatdinov N.N. Optimal design of chemical processes under uncertainty. Theor. Found. Chem. Eng. 2014. V. 48. N 5. P. 583–593. DOI: 10.1134/S0040579514050212.
Terrazas-Moreno S., Grossmann I.E., Wassick J.M. An efficient method for optimal design of large-scale integrated chemical production sites with endogenous uncertainty. Comp. Chem. Eng. 2012. V. 37. P. 89-103. DOI: 10.1016/j.compchemeng.2011.10.005.
Han Z.-Y., Xing R., Zhang D.-H. Vacuum pressure swing adsorption system for N2/CH4 separation under uncertainty. Chem. Eng. Res. Des. 2019. V. 142. P. 245–256. DOI: 10.1016/j.cherd.2018.12.017.
Biegler L., Jiang L., Fox V. Recent Advances in Simulation and Optimal Design of Pressure Swing Adsorption Systems. Sep. Purif. Rev. 2004. V. 33. N 1. P. 1–39. DOI: 10.1081/SPM-120039562.
Keltsev N.V. Fundamentals of adsorption technology. M.: Khimimya. 1984. 592 p.
Knaebel S.P., Ko D., Biegler L.T. Simulation and optimization of a pressure swing adsorption system: Recovering hydrogen from methane. Adsorption. 2005. V. 11(1 SUPPL.). P. 615-620. DOI: 10.1007/s10450-005-5994-4.
Xiao J., Li R., Bénard P. Heat and mass transfer model of multicomponent adsorption system for hydrogen purification. Int. J. Hydrogen Energy. 2015. V. 40. N 14. P. 4794-4803. DOI: 10.1016/j.ijhydene.2015.02.042.
Ribeiro A.M., Grande C.A., Lopes F.V. A parametric study of layered bed PSA for hydrogen purification. Chem. Eng. Sci. 2008. V. 63. N 21. P. 5258 – 5273. DOI: 10.1016/j.ces.2008.07.017.
Akulinin E.I., Golubyatnikov O.O., Dvoretsky D.S. Optimization and analysis of pressure swing adsorption process for oxygen production from air under uncertainty. Chem. Ind. Chem. Eng. Q. 2020. V. 26. N 1. P. 89–104. DOI: 10.2298/CICEQ190414028A.
Dubinin M.M. Fundamentals of the theory of adsorption in micropores of carbon adsorbents: Characteristics of their adsorption properties and microporous structures. Carbon. 1989. V. 27. N 3. P. 457–467. DOI: 10.1016/0008-6223(89)90078-X.
Dubinin M.M. Adsorption and porosity. M.: VAHZ. 1972. 128 p.
Reid R., Prausnitz J., Sherwood T. The properties of gases and liquids. McGraw-Hill. 1977. 707 p.
Moon D.-K., Lee D.-G., Lee C.-H. H2 pressure swing adsorption for high pressure syngas from an integrated gasification combined cycle with a carbon capture process. Appl. Energy. 2016. V. 183. P. 760-774. DOI: 10.1016/j.apenergy.2016.09.038.
Ergun S. Fluid flow through packed columns. Chem. Eng. Progress. 1952. V. 48. P. 89-94.
Jiang, L., Fox V.G., Biegler L.T. Simulation and optimal design of multiple-bed pressure swing adsorption systems. AIChE J. 2004. V. 50. N 11. P. 2904–2917. DOI: 10.1002/aic.10223.
Rudobashta S.P., Kosheleva M.K. The determination of mass transfer and mass conductivity coefficients from the kinetic curves. Izv. Vyssh. Uchebn. Zaved. Teknol. Tekstil. Promyshl. 2015. V. 360. N 6. P. 175–180.
Rudobashta S.P. Calculation of the kinetics of drying disperse materials on the basis of analytical methods. J. Eng. Phys. Thermophys. 2010. V. 83. N 4. P. 753–763. DOI: 10.1007/s10891-010-0394-3.
Lopes F.V., Grande C.A., Rodrigues A.E. Activated carbon for hydrogen purification by pressure swing adsorption: Multicomponent breakthrough curves and PSA performance. Chem. Eng. Sci. 2011. V. 66. N 3. P. 303-317. DOI: 10.1016/j.ces.2010.10.034.
Tavan Y., Hosseini S.H., Olazar M. A note on an inte-grated process of methane steam reforming in junction with pressure-swing adsorption to produce pure hydrogen: Mathematical modeling. Ind. Eng. Chem. Res. 2015. V. 54. N 51. P. 12937-12947. DOI: 10.1021/acs.iecr.5b01477.
Ohs B., Lohaus J., Marten D. Optimized hollow fiber sorbents and pressure swing adsorption process for H-2 recovery. Ind. Eng. Chem. Res. 2018. V. 57. N 14. P. 5093–5105. DOI: 10.1021/acs.iecr.7b05368.
Nogueira I.B., Martins M.A., Regufe M.J. Big Data-Based Optimization of a Pressure Swing Adsorption Unit for Syngas Purification: On Mapping Uncertainties from a Metaheuristic Technique. Ind. Eng. Chem. Res. 2020. V. 59. N 31. P. 14037-14047. DOI: 10.1021/acs.iecr.0c01155.
Rao V.R., Farooq S. Experimental study of a pulsed-pressure-swing-adsorption process with very small 5A zeo-lite particles for oxygen enrichment. Ind. Eng. Chem. Res. 2014. V. 53. N 33. P. 13157-13170. DOI: 10.1021/ie404199v.
Xiao J., Peng Y., Bénard P. Thermal effects on break-through curves of pressure swing adsorption for hydrogen purification. Int. J. Hydrogen Energy. 2016. V. 41. N 19. P. 8236-8245. DOI: 10.1016/j.ijhydene.2015.11.126.
Zhang N., Bénard P., Chahine R. Optimization of pressure swing adsorption for hydrogen purification based on Box-Behnken design method. Int. J. Hydrogen Energy. 2021. V. 46. N 7. P. 5403-5417. DOI: 10.1016/j.ijhydene.2020.11.045.
Ye F., Ma S., Tong L. Artificial neural network based optimization for hydrogen purification performance of pressure swing adsorption. Int. J. Hydrogen Energy. 2019. V. 44. N 11. P. 5334-5344. DOI: 10.1016/j.ijhydene.2018.08.104.
Ma S., Tong L., Ye F. Hydrogen purification layered bed optimization based on artificial neural network prediction of breakthrough curves. Int. J. Hydrogen Energy. 2019. V. 44. N 11. P. 5324-5333. DOI: 10.1016/j.ijhydene.2018.12.142.
Rambabu K., Muruganandam L., Velu S. CFD Simulation for Separation of Carbon Dioxide-Methane Mixture by Pressure Swing Adsorption. Int. J. Chem. Eng. 2014. P. 402756. DOI: 10.1155/2014/402756.
Gautier R., Dbouk T., Harion J.L. Pressure-swing-adsorption of gaseous mixture in isotropic porous medium: Numerical sensitivity analysis in CFD. Chem. Eng. Res. Des. 2018. V. 129. P. 314-326. DOI: 10.1016/j.cherd.2017.11.007.
Akulinin E.I., Golubyatnikov O.O., Dvoretsky D.S. Computational fluid dynamics modeling in a fixed adsor-bent layer during separation of gas mixtures. J. Phys.: Conf. Ser. 2020. V. 1153. N 1. P. 012004. DOI: 10.1088/1742-6596/1553/1/012004.
Zheng X., Liu Y., Liu W. Two-dimensional modeling of the transport phenomena in the adsorber during pressure swing adsorption process. Ind. Eng. Chem. Res. 2010. V. 49. N 22. DOI: 11814–11824. 10.1021/ie100474n.
Yang X., Wang H., Chen J. Two-dimensional modeling of pressure swing adsorption (PSA) oxygen generation with radial-flow adsorber. Appl. Sci. (Switzerland). 2019. V. 9. N 6. P. 1153. DOI: 10.3390/app9061153.
Zheng X.G., Yao H., Huang Y. Orthogonal numerical simulation on multifactor design for rapid pressure swing adsorption. Adsorption. 2017. V. 23. N 5. P. 685-697. DOI: 10.1007/s10450-017-9886-1.
Pan M., Omar H.M., Rohani S. Application of nanosize zeolite molecular sieves for medical oxygen concentration. Nanomaterials. 2017. V. 7. N 8. P. 195. DOI: 10.3390/nano7080195.
Santos C., Portugal A. F., Magalhaes F.D. Optimization of medical PSA units for oxygen production. Ind. Eng. Chem. Res. 2006. V. 45. P. 1085–1096. DOI: 10.1021/ie0504809.
Nikolic D., Kikkindes E. Modelling and optimization of hybrid PSA/membrane separation processes. Adsorption. 2015. V. 21. N 4. P. 283–305. DOI: 10.1007/s10450-015-9670-z.
Ohs B., Falkenberg M., Wessling M. Optimizing a hybrid membrane-pressure swing adsorption processes for bio-genic hydrogen recovery. Chem. Eng. J. 2019. V. 364. P. 452-461. DOI: 10.1016/j.cej.2019.01.136.
Kim S., Ko D., Moon I. Dynamic Optimization of a Dual Pressure Swing Adsorption Process for Natural Gas Purification and Carbon Capture. Ind. Eng. Chem. Res. 2016. V. 55. 12444. DOI: 10.1021/acs.iecr.5b04157.
Agarwal A., Biegler L.T., Zitney S.E. Simulation and optimization of pressure swing adsorption systems using reducedorder modeling. Ind. Eng. Chem. Res. 2009. V. 48. N 5. P. 2327-2343. DOI: 10.1021/ie071416p.
Boukoulava F., Hasan M., Floudas C. Global optimization of general constrained grey-box models: new method and its application to constrained PDEs for pressure swing adsorption. J. Global Optim. 2015. V. 67. N 1–2. P. 3–42. DOI: 10.1007/s10898-015-0376-2.
Akulinin E.I., Golubyatnikov O.O., Dvoretsky D.S. Optimizing pressure-swing adsorption processes and installations for gas mixture purification and separation. Chem. Eng. Transact. 2019. V. 74. P. 883-888. DOI: 10.3303/CET1974148.
Capra F., Gazzani M., Joss L. MO-MCS, a Derivative-Free Algorithm for the Multiobjective Optimization of Ad-sorption Processes. Ind. Eng. Chem. Res. 2018. V. 57. N 30. P. 9977-9993. DOI: 10.1021/acs.iecr.8b00207.
Sant Anna H.R., Barreto A.G., Tavares F.W. Machine learning model and optimization of a PSA unit for me-thane-nitrogen separation. Comp. Chem. Eng. 2017. V. 104. P. 377-391. DOI: 10.1016/j.compchemeng.2017.05.006.
Yu X., Shen Y., Guan Z. Multi-objective optimization of ANN-based PSA model for hydrogen purification from steam-methane reforming gas. Int. J. Hydrogen Energy. 2021. V. 46. N 21. P. 11740-11755. DOI: 10.1016/j.ijhydene.2021.01.107.
Samarskiy A.A., Labutin A.N., Labutina T.V. Modelling and analysis of carbon dioxide chemisorption process as object of control. ChemChemTech. [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2017. V. 60. N 8. P. 74-79. DOI: 10.6060/tcct.2017608.5622.
Lipin A.A., Nebukin V.O., Lipin A.G. Simulation of heat and mass transfer processes under granules capsulation in fluidized bed. ChemChemTech. [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2018. V. 61. N 4-5. P. 98-104. DOI: 10.6060/tcct.20186104-05.5624.
Akulinin E.I., Golubyatnikov O.O., Dvoretsky D.S. The optimal design of pressure swing adsorption process of air oxygen enrichment under uncertainty. Bulletin of the South Ural State University. Ser. Mathematical Modelling, Programming & Computer Software (Bulletin SUSU MMCS). 2020. V. 13. N. 2. P. 5–16. DOI: 10.14529/mmp200201.
Dvoretsky D.S., Dvoretsky S.I. Integrated design of flexible chemical processes, devices, and control systems. Theor. Found. Chem. Eng. 2014. V. 48. N. 5. P. 614–621. DOI: 10.1134/S0040579514050169.
