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dc.creatorArias, Ana Marisa
dc.creatorMores, Patricia Liliana
dc.creatorScenna, Nicolás José
dc.creatorCaballero, José Antonio
dc.creatorMussati, Sergio Fabián
dc.creatorMussati, Miguel Ceferino
dc.date.accessioned2024-04-03T17:29:56Z
dc.date.available2024-04-03T17:29:56Z
dc.date.issued2018-10-31
dc.identifier.citation. Processes, 6(11), Article 11es_ES
dc.identifier.issn2227-9717
dc.identifier.urihttp://hdl.handle.net/20.500.12272/10256
dc.description.abstractThis paper fits into the process system engineering field by addressing the optimization of a two-stage membrane system for H2 separation in refinery processes. To this end, a nonlinear mathematical programming (NLP) model is developed to simultaneously optimize the size of each membrane stage (membrane area, heat transfer area, and installed power for compressors and vacuum pumps) and operating conditions (flow rates, pressures, temperatures, and compositions) to achieve desired target levels of H2 product purity and H2 recovery at a minimum total annual cost. Optimal configuration and process design are obtained from a model which embeds different operating modes and process configurations. For instance, the following candidate ways to create the driving force across the membrane are embedded: (a) compression of both feed and/or permeate streams, or (b) vacuum application in permeate streams, or (c) a combination of (a) and (b). In addition, the potential selection of an expansion turbine to recover energy from the retentate stream (energy recovery system) is also embedded. For a H2 product purity of 0.90 and H2 recovery of 90%, a minimum total annual cost of 1.764 M$·year−1 was obtained for treating 100 kmol·h−1 with 0.18, 0.16, 0.62, and 0.04 mole fraction of H2, CO, N2, CO2, respectively. The optimal solution selected a combination of compression and vacuum to create the driving force and removed the expansion turbine. Afterwards, this optimal solution was compared in terms of costs, process-unit sizes, and operating conditions to the following two suboptimal solutions: (i) no vacuum in permeate stream is applied, and (ii) the expansion turbine is included into the process. The comparison showed that the latter (ii) has the highest total annual cost (TAC) value, which is around 7% higher than the former (i) and 24% higher than the found optimal solution. Finally, a sensitivity analysis to investigate the influence of the desired H2 product purity and H2 recovery is presented. Opposite cost-based trade-offs between total membrane area and total electric power were observed with the variations of these two model parameters. This paper contributes a valuable decision support tool in the process system engineering field for designing, simulating, and optimizing membranebased systems for H2 separation in a particular industrial case; and the presented optimization resultsprovide useful guidelines to assist in selecting the optimal configuration and operating mode.es_ES
dc.description.sponsorshipUniversidad Tecnológica Nacional (UTN) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)es_ES
dc.formatpdfes_ES
dc.language.isoenges_ES
dc.rightsopenAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.rights.uriAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.sourceProcesses, 6(11), Article 11es_ES
dc.subjectHidrógenoes_ES
dc.subjectProceso de separaciónes_ES
dc.subjectNLPes_ES
dc.subjectGAMSes_ES
dc.subjectIngeniería químicaes_ES
dc.titleOptimal design of a two-stage membrane system for hydrogen separation in refining processes.es_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.affiliationFil: Arias, Ana Marisa. Universidad Tecnológica Nacional. Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) ; Argentina.es_ES
dc.description.affiliationFil: Mores, Patricia Liliana. Universidad Tecnológica Nacional. Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) ; Argentina.es_ES
dc.description.affiliationFil: Scenna, Nicolás José. Universidad Tecnológica Nacional. Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) ; Argentina.es_ES
dc.description.affiliationFil: Caballero, José Antonio. University of Alicante. Department of Chemical Engineering ; España.es_ES
dc.description.affiliationFil : Mussati, Sergio Fabián. Consejo Nacional de investigaciones Científicas y Técnicas (CONICET). Instituto de Desarrollo y Diseño (INGAR) ; Argentina.es_ES
dc.description.affiliationFil: Mussati, Miguel Ceferino. Consejo Nacional de investigaciones Científicas y Técnicas (CONICET). Instituto de Desarrollo y Diseño (INGAR) ; Argentina.es_ES
dc.description.peerreviewedPeer Reviewedes_ES
dc.type.versionacceptedVersiones_ES
dc.rights.useAcceso abierto, con fines de estudio e investigación. Siempre con la mención de los autores.es_ES
dc.identifier.doihttps://doi.org/10.3390/pr6110208
dc.creator.orcid0000-0002-6716-6633es_ES
dc.creator.orcid0000-0001-6026-142Xes_ES
dc.creator.orcid0000-0002-1129-8725es_ES
dc.creator.orcid0000-0001-6470-2907es_ES
dc.creator.orcid0000-0002-4132-0292es_ES
dc.creator.orcid0000-0002-6104-5179es_ES


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