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Performance Assessment of a Concrete Gravity Dam at Shenwo Reservoir of China Using Deterministic and Probabilistic Methods

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Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: International Journal of Structural Stability and Dynamics, , n. 5, v. 14
Seite(n): 1440002
DOI: 10.1142/s0219455414400021
Abstrakt:

This paper performs degradation assessment and safety evaluation of a concrete gravity dam at Shenwo reservoir in Liaoning province of China by using two methods, i.e. deterministic method and probabilistic method, respectively. The deterministic responses of representative sluice piers are computed through static pushover and dynamic analyses. The probabilistic uncertainty analysis, including time invariant and time variant reliability analyses, is based on finite element (FE) reliability theory. For time invariant case, the material and loading parameters are considered as random variables, including elastic modulus, Poisson's ratio, mass density and pushover forces. For time variant case, the earthquake history is simulated by using random process, and the first_order reliability method (FORM) approximation combined with Koo's analytical solution is used to compute the mean upcrossing rate for given performance functions, through which the failure probabilities are calculated. Based on the analysis results using these two methods, the safety and reliability of the dam is assessed. Furthermore, the performance assessments of the dam in its current state are compared with those in the original state (i.e. when the dam was built) to quantify its performance degradation. Finally, the assessment results of using the deterministic and probabilistic methods are compared, and the discrepancies between them are quantified and explained. The computation is based on a general FE analysis platform for earthquake engineering simulation, OpenSees.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.1142/s0219455414400021.
  • Über diese
    Datenseite
  • Reference-ID
    10352738
  • Veröffentlicht am:
    14.08.2019
  • Geändert am:
    14.08.2019
 
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