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dc.contributor.authorVikse, Matias
dc.contributor.authorWatson, Harry AJ
dc.contributor.authorKim, Donghoi
dc.contributor.authorBarton, Paul I
dc.contributor.authorGundersen, Truls
dc.date.accessioned2021-10-27T20:34:23Z
dc.date.available2021-10-27T20:34:23Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/136230
dc.description.abstract© 2020 The Authors This article uses a nonsmooth flowsheeting methodology to create simulation and optimization models for dual mixed refrigerant processes. New improved operating conditions are obtained using the primal-dual interior-point optimizer IPOPT, with sensitivity information calculated using new developments in nonsmooth analysis to obtain generalized derivative information using a nonsmooth generalization of the vector forward mode of automatic differentiation. Several optimization studies are performed with constraints on both the minimum temperature difference (ΔTmin) and total heat exchanger conductance (UAmax) used to represent the trade-offs between energy consumption and the required heat transfer area. In addition, comparison is made with the conventional process simulator Aspen HYSYS using particle swarm optimization. Results show that the nonsmooth model was able to reduce the required compression power by 14.4% compared to the initial feasible design for the dual mixed refrigerant process, and by 20.4–21.6% for the dual mixed refrigerant process with NGL extraction. Furthermore, the solutions obtained from the nonsmooth model were 1.9–8.1% better than the design obtained by particle swarm optimization. Multistart optimization also shows that IPOPT converges to the best known solution when starting from an initial feasible design.
dc.language.isoen
dc.publisherElsevier BV
dc.relation.isversionof10.1016/J.ENERGY.2020.116999
dc.rightsCreative Commons Attribution 4.0 International license
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceElsevier
dc.titleOptimization of a dual mixed refrigerant process using a nonsmooth approach
dc.typeArticle
dc.contributor.departmentMassachusetts Institute of Technology. Process Systems Engineering Laboratory
dc.relation.journalEnergy
dc.eprint.versionFinal published version
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/PeerReviewed
dc.date.updated2021-06-07T15:12:41Z
dspace.orderedauthorsVikse, M; Watson, HAJ; Kim, D; Barton, PI; Gundersen, T
dspace.date.submission2021-06-07T15:12:43Z
mit.journal.volume196
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Needed


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