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Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic

Climate change, energy transition, population growth and other natural and anthropogenic impacts, combined with outdated (unfashionable) infrastructure, can force Dam and Reservoir Systems (DRS) operation outside of the design envelope (adverse operating conditions).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 re...

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Autores principales: Milašinović, Miloš, Ivetić, Damjan, Stojković, Milan, Savić, Dragan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885076/
http://dx.doi.org/10.1007/s11269-022-03420-w
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author Milašinović, Miloš
Ivetić, Damjan
Stojković, Milan
Savić, Dragan
author_facet Milašinović, Miloš
Ivetić, Damjan
Stojković, Milan
Savić, Dragan
author_sort Milašinović, Miloš
collection PubMed
description Climate change, energy transition, population growth and other natural and anthropogenic impacts, combined with outdated (unfashionable) infrastructure, can force Dam and Reservoir Systems (DRS) operation outside of the design envelope (adverse operating conditions).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. GRAPHICAL ABSTRACT: [Image: see text]
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spelling pubmed-98850762023-01-30 Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic Milašinović, Miloš Ivetić, Damjan Stojković, Milan Savić, Dragan Water Resour Manage Article Climate 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. GRAPHICAL ABSTRACT: [Image: see text] Springer Netherlands 2023-01-30 2023 /pmc/articles/PMC9885076/ http://dx.doi.org/10.1007/s11269-022-03420-w Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Milašinović, Miloš
Ivetić, Damjan
Stojković, Milan
Savić, Dragan
Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic
title Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic
title_full Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic
title_fullStr Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic
title_full_unstemmed Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic
title_short Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic
title_sort failure conditions assessment of complex water systems using fuzzy logic
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885076/
http://dx.doi.org/10.1007/s11269-022-03420-w
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