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dc.contributor.authorChung, Wonsuk-
dc.contributor.authorAl-Hunaidy, Ali S.-
dc.contributor.authorImran, Hasan-
dc.contributor.authorLee, Jay H.-
dc.date.accessioned2024-04-24T07:40:48Z-
dc.date.available2024-04-24T07:40:48Z-
dc.date.created2024-04-18-
dc.date.issued2023-07-
dc.identifier.issn2405-8963-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/149719-
dc.description.abstractSynthesis of sustainable processing pathway is an important initial step in deciding investments in carbon capture, utilization, and sequestration (CCUS). For a best decision, it is necessary to analyze a very large number of potential processing pathways at once in terms of their economics and net carbon emission. Such analysis may also reveal which parts of a pathway incur significant portions of the costs and carbon emissions, suggesting hotspots for improvement. Frameworks used should also be flexible enough to accommodate varying feed conditions and market/emission data as they tend to vary according to the sources of CO2 and geographical locations. The superstructure method along with a state-task network (STN) representation offers such flexibility in analyzing a CCUS system. This work proposes to use a STN representation of a process in a superstructure composed of feeds, processes, and products, to represent and optimize among various options of CCUS pathways through mathematical programming. A case study is conducted to illustrate the utility of the STN representation in the CCUS superstructure optimization. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)-
dc.languageEnglish-
dc.publisherELSEVIER-
dc.titleSynthesis of carbon capture, utilization, and sequestration processing pathways using state-task network representation-
dc.typeConference-
dc.identifier.doi10.1016/j.ifacol.2023.10.492-
dc.description.journalClass1-
dc.identifier.bibliographicCitation22nd World Congress of the International Federation of Automatic Control (IFAC), pp.6888 - 6893-
dc.citation.title22nd World Congress of the International Federation of Automatic Control (IFAC)-
dc.citation.startPage6888-
dc.citation.endPage6893-
dc.citation.conferencePlaceNE-
dc.citation.conferencePlaceYokohama, JAPAN-
dc.citation.conferenceDate2023-07-09-
dc.relation.isPartOfIFAC PAPERSONLINE-
dc.identifier.wosid001122557300101-
dc.identifier.scopusid2-s2.0-85184959145-
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KIST Conference Paper > 2023
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