Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Sensitivity of uncertainties in performance prediction of deteriorating concrete structures
Deterioration models for the condition and reliability prediction of civil infrastructure facilities involve numerous assumptions and simplifications. Furthermore, input parameters of these models are fraught with uncertainties. A Bayesian methodology has been developed by the authors, which uses information obtained through health monitoring to improve the quality of prediction. The sensitivity of prior and posterior predicted performance to different input parameters of the deterioration models, and the effect of instrument and measurement uncertainty, is investigated in this paper. The results quantify the influence of these uncertainties and highlight the efficacy of the updating methodology based on integrating monitoring data. It has been found that the probabilistic posterior performance predictions are significantly less sensitive to most of the input uncertainties. Furthermore, updating the performance distribution based on ‘event’ outcomes is likely to be more beneficial than monitoring and updating of the input parameters on an individual basis.
Sensitivity of uncertainties in performance prediction of deteriorating concrete structures
Deterioration models for the condition and reliability prediction of civil infrastructure facilities involve numerous assumptions and simplifications. Furthermore, input parameters of these models are fraught with uncertainties. A Bayesian methodology has been developed by the authors, which uses information obtained through health monitoring to improve the quality of prediction. The sensitivity of prior and posterior predicted performance to different input parameters of the deterioration models, and the effect of instrument and measurement uncertainty, is investigated in this paper. The results quantify the influence of these uncertainties and highlight the efficacy of the updating methodology based on integrating monitoring data. It has been found that the probabilistic posterior performance predictions are significantly less sensitive to most of the input uncertainties. Furthermore, updating the performance distribution based on ‘event’ outcomes is likely to be more beneficial than monitoring and updating of the input parameters on an individual basis.
Sensitivity of uncertainties in performance prediction of deteriorating concrete structures
Rafiq, M. Imran (Autor:in) / Onoufriou, Toula (Autor:in) / Chryssanthopoulos, Marios (Autor:in)
Structure and Infrastructure Engineering ; 2 ; 117-130
01.06.2006
14 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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