In risk assessment of spatially distributed infrastructure, the probability of demand exceeding capacity is evaluated across the system. We describe and compare two levee system reliability analysis frameworks for seismic and high-water demands. The first approach is general, but computationally intensive, and uses Monte Carlo simulations to model capacity and demand for “segments” (i.e., elemental levee lengths) as spatially correlated random variables. We apply a capacity correlation model derived from seismic case histories in Japan. The seismic demand correlation model is based on global ground motion data, whereas the high-water correlation is taken as unity. The second approach achieves computational efficiency by grouping segments into physics-based “reaches” (i.e., length of levee having uniform statistical distributions of capacity and demand). Statistics and spatial correlation of the limit state function are computed using a procedure based on the first-order reliability method. The probability of failure of the reach is then computed using level-crossing statistics. The application of level crossing statistics required an adjustment, introduced here, to previously utilized capacity correlation functions. We apply both methods for a levee system subjected to realistic demand and capacity distributions and show that characteristic lengths (defined as lengths of levee that can be considered as statistically independent) are comparable for high-water and seismic demands. This outcome is specific to the considered failure mechanisms and is driven by use of similar capacity correlation models, whereas differences in demand correlation models have limited impact.

Multi-hazard system reliability of flood control levees

Zimmaro P.
;
2019

Abstract

In risk assessment of spatially distributed infrastructure, the probability of demand exceeding capacity is evaluated across the system. We describe and compare two levee system reliability analysis frameworks for seismic and high-water demands. The first approach is general, but computationally intensive, and uses Monte Carlo simulations to model capacity and demand for “segments” (i.e., elemental levee lengths) as spatially correlated random variables. We apply a capacity correlation model derived from seismic case histories in Japan. The seismic demand correlation model is based on global ground motion data, whereas the high-water correlation is taken as unity. The second approach achieves computational efficiency by grouping segments into physics-based “reaches” (i.e., length of levee having uniform statistical distributions of capacity and demand). Statistics and spatial correlation of the limit state function are computed using a procedure based on the first-order reliability method. The probability of failure of the reach is then computed using level-crossing statistics. The application of level crossing statistics required an adjustment, introduced here, to previously utilized capacity correlation functions. We apply both methods for a levee system subjected to realistic demand and capacity distributions and show that characteristic lengths (defined as lengths of levee that can be considered as statistically independent) are comparable for high-water and seismic demands. This outcome is specific to the considered failure mechanisms and is driven by use of similar capacity correlation models, whereas differences in demand correlation models have limited impact.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/305807
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