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Numerical Research on the Pressure Swing Adsorption Process

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Processes 2022, 10, 812 18 of 19 36. Zhou, L.; Qu, Z.G.; Chen, L.; Tao, W.Q. Lattice Boltzmann simulation of gas-solid adsorption processes at pore scale level. J. Comput. Phys. 2015, 300, 800–813. [CrossRef] 37. Weber, T.W.; Chakravorti, R.K. Pore and solid diffusion models for fixed-bed adsorbers. AIChE J. 1974, 20, 228–238. [CrossRef] 38. Inglezakis, V.J.; Fyrillas, M.M.; Park, J. Variable diffusivity homogeneous surface diffusion model and analysis of merits and fallacies of simplified adsorption kinetics equations. J. Hazard. Mater. 2019, 367, 224–245. [CrossRef] 39. Haerifar, M.; Azizian, S. An exponential kinetic model for adsorption at solid/solution interface. Chem. Eng. J. 2013, 215, 65–71. [CrossRef] 40. Li, Z.; Liu, Y.; Wang, H.; Tsai, C.-J.; Yang, X.; Xing, Y.; Zhang, C.; Xiao, P.; Webley, P.A. A numerical modelling study of SO2 adsorption on activated carbons with new rate equations. Chem. Eng. J. 2018, 353, 858–866. [CrossRef] 41. Ma, Q.; Chen, Z.; Liu, H. 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Energy and productivity efficient vacuum pressure swing adsorption process to separate CO2 from CO2/N2 mixture using Mg-MOF-74: A CFD simulation. Appl. Energy 2018, 209, 190–202. [CrossRef] 47. Ali Abd, A.; Roslee Othman, M.; Helwani, Z. Evaluation of thermal effects on carbon dioxide breakthrough curve for biogas upgrading using pressure swing adsorption. Energy Convers. Manag. 2021, 247, 114752. [CrossRef] 48. Ebner, A.D.; Mehrotra, A.; Ritter, J.A. Graphical approach for complex PSA cycle scheduling. Adsorption 2009, 15, 406–421. [CrossRef] 49. Ebner, A.D.; Mehrotra, A.; Ritter, J.A. Graphical unit block approach for complex PSA cycle scheduling of parallel interacting trains of columns and tanks. Adsorption 2015, 21, 229–241. [CrossRef] 50. Mehrotra, A.; Ebner, A.D.; Ritter, J.A. Simplified graphical approach for complex PSA cycle scheduling. Adsorption 2011, 17, 337–345. [CrossRef] 51. Ebner, A.D.; Ho, J.G.S.; Ritter, J.A. Graphical approach for formulating pressure swing adsorption cycle schedules with unlimited equalization steps. Adsorption 2018, 24, 221–232. [CrossRef] 52. Park, Y.; Kang, J.H.; Moon, D.K.; Jo, Y.S.; Lee, C.H. Parallel and series multi-bed pressure swing adsorption processes for H2 recovery from a lean hydrogen mixture. Chem. Eng. J. 2021, 408, 127299. [CrossRef] 53. Liu, B.; Yu, X.; Shi, W.; Shen, Y.; Zhang, D.; Tang, Z. Two-stage VSA/PSA for capturing carbon dioxide (CO2) and producing hydrogen (H2) from steam-methane reforming gas. Int. J. Hydrogen Energy 2020, 45, 24870–24882. [CrossRef] 54. Lu, B.; Shen, Y.; Tang, Z.; Zhang, D.; Chen, G. Vacuum pressure swing adsorption process for coalbed methane enrichment. Chin. J. Chem. Eng. 2021, 32, 264–280. [CrossRef] 55. Golmakani, A.; Nabavi, S.A.; Manovic ́, V. Production of negative-emission biomethane by twin double-bed pressure swing adsorption with tail gas sequestration. Chem. Eng. J. 2021, 408, 127312. [CrossRef] 56. Chen, Y.-F.; Lin, P.-W.; Chen, W.-H.; Yen, F.-Y.; Yang, H.-S.; Chou, C.-T. Biogas Upgrading by Pressure Swing Adsorption with Design of Experiments. Processes 2021, 9, 1325. [CrossRef] 57. Van Chinh, P.; Hieu, N.T.; Tien, V.D.; Nguyen, T.-Y.; Nguyen, H.N.; Anh, N.T.; Thom, D. Van Simulation and Experimental Study of a Single Fixed-Bed Model of Nitrogen Gas Generator Working by Pressure Swing Adsorption. Processes 2019, 7, 654. [CrossRef] 58. Durán, I.; Rubiera, F.; Pevida, C. Modeling a biogas upgrading PSA unit with a sustainable activated carbon derived from pine sawdust. Sensitivity analysis on the adsorption of CO2 and CH4 mixtures. Chem. Eng. J. 2022, 428, 132564. [CrossRef] 59. Subraveti, S.G.; Li, Z.; Prasad, V.; Rajendran, A. Machine learning-based multiobjective optimization of pressure swing adsorption. Ind. Eng. Chem. Res. 2019, 58, 20412–20422. [CrossRef] 60. Rebello, C.M.; Martins, M.A.F.; Rodrigues, A.E.; Loureiro, J.M.; Ribeiro, A.M.; Nogueira, I.B.R. A novel standpoint of Pressure Swing Adsorption processes multi-objective optimization: An approach based on feasible operation region mapping. Chem. Eng. Res. Des. 2022, 178, 590–601. [CrossRef] 61. Capra, F.; Gazzani, M.; Joss, L.; Mazzotti, M.; Martelli, E. MO-MCS, a derivative-free algorithm for the multiobjective optimization of adsorption processes. Ind. Eng. Chem. Res. 2018, 57, 9977–9993. [CrossRef] 62. Yang, L.; Zhu, A.; Shao, J.; Chi, T. A knowledge-informed and pareto-based artificial bee colony optimization algorithm for multi-objective land-use allocation. ISPRS Int. J. Geo-Inf. 2018, 7, 63. [CrossRef] 63. Khajuria, H.; Pistikopoulos, E.N. Optimization and control of pressure swing adsorption processes under uncertainty. AIChE J. 2013, 59, 120–131. [CrossRef] 64. Nilchan, S.; Pantelides, C.C. On the optimisation of periodic adsorption processes. Adsorption 1998, 4, 113–147. [CrossRef] 65. Tsay, C.; Pattison, R.C.; Baldea, M. A pseudo-transient optimization framework for periodic processes: Pressure swing adsorption and simulated moving bed chromatography. AIChE J. 2018, 64, 2982–2996. [CrossRef]

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