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dc.contributor.authorBahrami, Mahdi
dc.contributor.authorRoghani, Bardia
dc.contributor.authorTscheikner-Gratl, Franz
dc.contributor.authorRokstad, Marius Møller
dc.date.accessioned2024-05-03T08:33:06Z
dc.date.available2024-05-03T08:33:06Z
dc.date.created2024-04-29T09:54:29Z
dc.date.issued2024
dc.identifier.issn0043-1354
dc.identifier.urihttps://hdl.handle.net/11250/3128961
dc.description.abstractGreen Infrastructure has transformed traditional urban stormwater management systems by fostering a wide range of service functions. Despite their popularity, green infrastructure's performance can deteriorate over their lifecycle, leading to operational failures. The operation of green infrastructure has predominantly relied on reactive maintenance strategies. To anticipate malfunctions and enhance the performance of green infrastructure in the long run, failure data needs to be recorded so that deterioration processes and component vulnerabilities can be recognized, modelled and included in predictive maintenance schemes. This study investigates possible failures in representative GIs and provides insights into the most important events that should be prioritized in the data collection process. A method for qualitative Fault Tree Analysis using minimal cut sets are introduced, aiming to identify potential failures with the minimum number of events. To identify events of interest fault trees were constructed for bioswales, rain gardens and green roofs, for three groups of service function failures, namely runoff quantity control, runoff quality control and additional service functions. The resulting fault trees consisted of 45 intermediate and 54 basic events. The minimal cut set analysis identified recurring basic events that could affect operation among all three green infrastructure instances. These events are ‘trash accumulation’, ‘clogging due to sediment accumulation’, and ‘overly dense vegetation’. Among all the possible cut sets, events such as ‘plants not thriving’, ‘invasive plants taking over’, and ‘deterioration caused by external influences’ could potentially disrupt most of the service functions green infrastructure provides. Furthermore, the analysis of interactions between component failures shows vegetation and filter media layer failures have the highest influence over other components. The constructed fault trees and identified basic events could be potentially employed for additional research on data collection processes and calculating the failure rates of green infrastructure and as a result, contribute to a shift toward their proactive operation and maintenance.en_US
dc.description.abstractA Deep Dive into Green Infrastructure Failures using Fault Tree Analysisen_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleA Deep Dive into Green Infrastructure Failures using Fault Tree Analysisen_US
dc.title.alternativeA Deep Dive into Green Infrastructure Failures using Fault Tree Analysisen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionsubmittedVersionen_US
dc.source.journalWater Researchen_US
dc.identifier.doi10.1016/j.watres.2024.121676
dc.identifier.cristin2265310
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode2


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal