Evaluating network reduction strategies for consistent risk assessment of critical infrastructures

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dc.catalogadorpau
dc.contributor.authorLlera Martin, Juan Carlos de la
dc.contributor.authorMonsalve M., Mauricio
dc.contributor.authorFerrario, Elisa
dc.contributor.authorAlberto, Yolanda
dc.contributor.authorArróspide, Felipe
dc.contributor.authorCastro, Sebastián
dc.contributor.authorPoulos, Alan
dc.date.accessioned2023-03-13T18:26:41Z
dc.date.available2023-03-13T18:26:41Z
dc.date.issued2020
dc.description.abstractCritical infrastructure networks are continuously growing, gaining complexity with each urban sprawl, conurbation, technological change, and regulatory update. Consequently, their detailed risk analysis demands large amounts of data, computational resources (required by simulations, optimization, flow equilibria, etc.), and dealing with complex interpretations of the results. This comes with several drawbacks: scarcity of adequately curated data, which instead are usually incomplete and sometimes even incorrect, algorithmic runtime that impairs the full use of Monte Carlo simulations, errors that may propagate extensively, and results that cannot be generalized and extended to other cases. Therefore, researchers have also resorted to analyzing simplified versions of these infrastructure systems. This work evaluates three algorithms for reducing the complexity of infrastructure networks while keeping reasonable accuracy for statistical interpretation. These algorithms transform a detailed graph into a more compact representation, where risk assessments can be performed more easily. The strategies used herein are based on the detection of important edges (backbone detection) and the merging or lumping similar or proximate elements (clustering, contractions). The different complexity reduction algorithms are evaluated on three infrastructure networks, namely: the electric transmission network of Chile, the electric distribution network of the Greater Valparaíso and the drinking water distribution network of the Greater Valparaíso. The experiments show that two of the three graph reduction criteria proposed in this work yield good approximations of the connectivity of the original graphs, when these are reduced to 25% of their size.
dc.fechaingreso.objetodigital2023-03-13
dc.format.extent8 páginas
dc.fuente.origenSIPA
dc.identifier.urihttps://www.cigiden.cl/evaluating-network-reduction-strategies-for-consistent-risk-assessment-of-critical-infrastructures/
dc.identifier.urihttps://www.rpsonline.com.sg/proceedings/esrel2020/html/5115.xml
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/66561
dc.information.autorucEscuela de Ingeniería; Llera Martin, Juan Carlos de la; 0000-0002-9064-0938; 53086
dc.language.isoen
dc.nota.accesoContenido completo
dc.relation.ispartofEuropean Safety and Reliability Conference and the Probabilistic Safety Assessment and Management Conference (30° y 15° ; 2020 ; Venecia, Italia
dc.rightsacceso restringido
dc.subjectCritical infrastructure
dc.subjectNetwork reduction
dc.subjectSparsification
dc.subjectCoarsening
dc.subjectBackbone extraction
dc.subjectClustering
dc.subject.ddc620
dc.subject.deweyIngenieríaes_ES
dc.titleEvaluating network reduction strategies for consistent risk assessment of critical infrastructureses_ES
dc.typecomunicación de congreso
sipa.codpersvinculados53086
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