EfficientUncertaintyQuantificationforComplexSystemsAnalysisMichaelBeerInstituteforRisk and Reliability,Leibniz UniversityHannover,GermanyInstituteforRiskandUncertainty,UniversityofLiverpool,UKInternational JointResearchCenterforEngineeringReliability andStochasticMechanics(ERSM),TongjiUniversity,China
Michael Beer 1 / 24 Efficient Uncertainty Quantification for Complex Systems Analysis Michael Beer Institute for Risk and Reliability, Leibniz University Hannover, Germany Institute for Risk and Uncertainty, University of Liverpool, UK International Joint Research Center for Engineering Reliability and Stochastic Mechanics (ERSM), Tongji University, China
ReliabilityAssessmentofComplexSystemsinUncertainEnvironmentsCOMPLEXNETWORKEDSYSTEMSDependenceoncomplexnetworksconstantlygrows.increasing demand for modern networks to be highly reliablequantifythedegreeto whichanetworkisabletoprovide itsserviceunderstandnetworkbehaviorforreliableandefficientpredictionspower western USfinancial globalgas distribution EuropeGrand challengesmodelinterdependencebetweendifferentnetworksefficient simulation tools and uncertainty quantification methodsdynamicnatureof real-worldnetworksprocessesonnetworks(e.g.epidemics,cascadingfailures)MichaelBeer2/24
Michael Beer 2 / 24 COMPLEX NETWORKED SYSTEMS Dependence on complex networks constantly grows quantify the degree to which a network is able to provide its service understand network behavior for reliable and efficient predictions increasing demand for modern networks to be highly reliable dynamic nature of real-world networks model interdependence between different networks efficient simulation tools and uncertainty quantification methods processes on networks (e.g. epidemics, cascading failures) Reliability Assessment of Complex Systems in Uncertain Environments • • • Grand challenges gas distribution Europe power western US financial global
ReliabilityAssessmentofComplexSystemsinUncertainEnvironmentsENGINEEREDSYSTEMS:SPECIFICCHALLENGESRapidgrowthinscale,complexityandinterconnectionuncertaintiesandrisksappearto agreaterextentthan everbeforeincreasingvulnerabilityandlackof resilience;seeFukushima,financial crisis,cybercrime,...low-probability-high-conseguenceeventsvery difficulttoidentifybuthighlycritical;dramaticconsequencesthroughcascadingfailuresissuesspanacrossdisciplinesApproachesofUncertaintyQuantificationAdvancedMonte CarloGeneralizedmodelsStochasticModelingSimulationmethodsforvagueand impreciseinformation, x(h,) d(o)X(t,w)4μ(x) 41.0eiSe]/htXeX=MichaelBeer3/24
Michael Beer 3 / 24 Rapid growth in scale, complexity and interconnection uncertainties and risks appear to a greater extent than ever before low-probability-high-consequence events very difficult to identify but highly critical; dramatic consequences through cascading failures increasing vulnerability and lack of resilience; see Fukushima, financial crisis, cyber crime, . issues span across disciplines ENGINEERED SYSTEMS: SPECIFIC CHALLENGES Approaches of Uncertainty Quantification Advanced Stochastic Modeling Monte Carlo Simulation methods Generalized models for vague and imprecise information Reliability Assessment of Complex Systems in Uncertain Environments
EfficientSystemsReliabilityAnalysisANALYSISOECOMPLEXSYSTEMSReliability,optimalmaintenanceandrepairmphatiguetestinMalorusChargvettonBanen2900DriveBeltbernanea.cmmo.comGasuneollTrteparatioMichael Beer4/24
Michael Beer 4 / 24 Reliability, optimal maintenance and repair ANALYSIS OF COMPLEX SYSTEMS Efficient Systems Reliability Analysis
EfficientSystemsReliabilityAnalysisANALYSISOECOMPLEXSYSTEMSModelingfor efficient and realisticreliability analysistraditionalapproachesTopevent》faulttreeanalysis》reliabilityblockdiagrams>》limitations in modeling》dependencies》common-causefailures》time-dependentbehavior》lackofinformation》complexnetworkstructurealternativemodelingtoaddresslimitationsimprovedreliabilityandavailabilityanalysisof systems》identifyweakcomponents》defineoptimalmaintenance strategiesMichaelBeer5/24
Michael Beer 5 / 24 ANALYSIS OF COMPLEX SYSTEMS Modeling for efficient and realistic reliability analysis Efficient Systems Reliability Analysis • traditional approaches » fault tree analysis alternative modeling to address limitations » reliability block diagrams » . limitations in modeling » dependencies » common-cause failures » time-dependent behavior » lack of information » complex network structure improved reliability and availability analysis of systems » identify weak components » define optimal maintenance strategies