Effect of Seismic and Soil Parameter Uncertainties on Seismic Damage of Buried Segmented Pipeline

Pipeline is one of the critical infrastructures in today civilization and spreads over a large area with varying soil conditions. The failure in pipe network causes significant economy losses to asset owners and environmental impact to the society. Therefore, it is important to ensure the safe operation of a pipe network during its lifetime. The structural performance (i.e., static and dynamic) of the buried pipeline largely depends on the pipe-soil interaction along the pipe segments. The soil shear strength properties (i.e., soil cohesion, density and friction angle) and its variability have been widely recognized as critical factors, which control the seismic performance of buried pipeline. These parameters are frequently considered independently in many studies, but in natural soil, the parameters are most likely to have strong dependency, which have significant influence in the seismic performance of buried pipe. Additionally, pipe seismic performance is also influenced by variability in ground motion parameters (e.g., wave propagation length, ground particle velocity, phase velocity of wave, etc). Thus, this study aims to stochastically evaluate the influence of soil uncertainties and variability in seismic parameters on seismic performance of buried segmented pipeline. Bivariate random field is used to probabilistically sample the cross-correlated soil parameters via Monte Carlo Simulations. The nonlinear finite element (FE) models are developed to simulate the axial joint-failure of segmented cast-iron (CI) pipelines with lead-caulked joint. The probabilistic seismic demand model (PSDM) is developed between repair rate (RR) per km to maximum ground strain by considering seismic wave with various wave propagation lengths. Furthermore, the effect of soil variabilities and seismic wave propagation lengths in seismic demand parameters are presented. Finally, for the PSDM can be implemented for rapid seismic damage estimate for buried pipe.


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  • Accession Number: 01716975
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Sep 2 2019 3:03PM