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dc.contributor.authorMilašinović, M
dc.contributor.authorIvetić, D
dc.contributor.authorStojković, M
dc.contributor.authorSavić, D
dc.date.accessioned2023-01-30T09:52:31Z
dc.date.issued2023-01-30
dc.date.updated2023-01-30T07:51:36Z
dc.description.abstractClimate change, energy transition, population growth and other natural and anthropogenic impacts, combined with outdated (unfashionable) infrastructure, can force Dam and Reservoir Systems (DRS) operation outside of the design envelope (adverse operating conditions). Since there is no easy way to redesign or upgrade the existing DRSs to mitigate against all the potential failure situations, Digital Twins (DT) of DRSs are required to assess system’s performance under various what-if scenarios. The current state of practice in failure modelling is that failures (system’s not performing at the expected level or not at all) are randomly created and implemented in simulation models. That approach helps in identifying the riskiest parts (subsystems) of the DRS (risk-based approach), but does not consider hazards leading to failures, their occurrence probabilities or subsystem failure exposure. To overcome these drawbacks, this paper presents a more realistic failure scenario generator based on a causal approach. Here, the novel failure simulation approach utilizes fuzzy logic reasoning to create DRS failures based on hazard severity and subsystems’ reliability. Combined with the system dynamics (SD) model this general failure simulation tool is designed to be used with any DRS. The potential of the proposed method is demonstrated using the Pirot DRS case study in Serbia over a 10-year simulation period. Results show that even occasional hazards (as for more than 97% of the simulation there were no hazards), combined with outdated infrastructure can reduce DRS performance by 50%, which can help in identifying possible “hidden” failure risks and support system maintenance prioritization.en_GB
dc.description.sponsorshipScience Fund of the Republic of Serbiaen_GB
dc.description.sponsorshipSerbian Ministry of Education, Science and Technological Developmenten_GB
dc.identifier.citationPublished online 30 January 2023en_GB
dc.identifier.doihttps://doi.org/10.1007/s11269-022-03420-w
dc.identifier.grantnumber6062556en_GB
dc.identifier.grantnumber451–03-68/2022–14/200092en_GB
dc.identifier.urihttp://hdl.handle.net/10871/132366
dc.identifierORCID: 0000-0001-9567-9041 (Savić, Dragan)
dc.identifierScopusID: 35580202000 (Savić, Dragan)
dc.identifierResearcherID: G-2071-2012 | L-8559-2019 (Savić, Dragan)
dc.language.isoenen_GB
dc.publisherSpringeren_GB
dc.rights.embargoreasonUnder embargo until 30 January 2024 in compliance with publisher policyen_GB
dc.rights© The Author(s), under exclusive licence to Springer Nature B.V. 2023en_GB
dc.subjectWater resources resilienceen_GB
dc.subjectDigital twinsen_GB
dc.subjectFailure modesen_GB
dc.subjectSystem dynamics modelen_GB
dc.titleFailure Conditions Assessment of Complex Water Systems Using Fuzzy Logicen_GB
dc.typeArticleen_GB
dc.date.available2023-01-30T09:52:31Z
dc.identifier.issn0920-4741
dc.descriptionThis is the author accepted manuscript. The final version is available from Springer via the DOI in this recorden_GB
dc.descriptionData Availability: All data and materials used in the research are documented within the manuscript.en_GB
dc.identifier.eissn1573-1650
dc.identifier.journalWater Resources Managementen_GB
dc.relation.ispartofWater Resources Management
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2022-12-27
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2023-01-30
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-01-30T09:49:58Z
refterms.versionFCDAM
refterms.panelBen_GB
refterms.dateFirstOnline2023-01-30


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