Multiscale modeling of fiber deformation: Application to a batch pulp digester for model predictive control of fiber strength

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dc.contributor.authorJung, Juyeongko
dc.contributor.authorChoi, Hyun-Kyuko
dc.contributor.authorSon, Sang Hwanko
dc.contributor.authorKwon, Joseph Sang-Ilko
dc.contributor.authorLee, Jay H.ko
dc.date.accessioned2022-04-15T06:44:31Z-
dc.date.available2022-04-15T06:44:31Z-
dc.date.created2022-03-10-
dc.date.created2022-03-10-
dc.date.created2022-03-10-
dc.date.created2022-03-10-
dc.date.created2022-03-10-
dc.date.issued2022-02-
dc.identifier.citationCOMPUTERS & CHEMICAL ENGINEERING, v.158-
dc.identifier.issn0098-1354-
dc.identifier.urihttp://hdl.handle.net/10203/294772-
dc.description.abstractLightweight packaging in the pulp and paper industry has received much attention as an effective way to reduce CO2 emissions. One challenge is that the tensile strength of packaging papers, which determines the maximum load, has to be comparable to that of conventional packaging materials. In a pulp digester, wood fibers are chemically separated and physically deformed during pulping, resulting in the dynamic change of tensile strength of end-use papers. In this work, the deformation of fiber during Kraft pulping is described by integrating the multiscale modeling framework of Choi and Kwon (2019a) and the classical column buckling theory. Then, an approximate model is identified and employed to design a model predictive control system to regulate the fiber deformation during pulping. The proposed control system achieved a lower degree of fiber deformation than a conventional pulping strategy, thereby contributing to the enhanced tensile strength of end-use papers. (C) 2021 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.titleMultiscale modeling of fiber deformation: Application to a batch pulp digester for model predictive control of fiber strength-
dc.typeArticle-
dc.identifier.wosid000754557800002-
dc.identifier.scopusid2-s2.0-85122161787-
dc.type.rimsART-
dc.citation.volume158-
dc.citation.publicationnameCOMPUTERS & CHEMICAL ENGINEERING-
dc.identifier.doi10.1016/j.compchemeng.2021.107640-
dc.contributor.localauthorLee, Jay H.-
dc.contributor.nonIdAuthorChoi, Hyun-Kyu-
dc.contributor.nonIdAuthorSon, Sang Hwan-
dc.contributor.nonIdAuthorKwon, Joseph Sang-Il-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorMultiscale model-
dc.subject.keywordAuthorModel predictive control-
dc.subject.keywordAuthorKinetic monte carlo-
dc.subject.keywordAuthorPulp digester-
dc.subject.keywordAuthorFiber curl-
dc.subject.keywordAuthorFiber deformation-
dc.subject.keywordPlusINFERENTIAL CONTROL-
dc.subject.keywordPlusCRYSTAL SHAPE-
dc.subject.keywordPlusIDENTIFICATION-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordPlusDECOMPOSITION-
dc.subject.keywordPlusUNCERTAINTY-
dc.subject.keywordPlusSIMULATION-
dc.subject.keywordPlusFLOW-
dc.subject.keywordPlusWOOD-
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