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Effect of Spatial Variability on the Reliability-Based Design of Drilled Shafts
In this paper, two probabilistic approaches for implementing the reliability-based design of drilled shafts considering the spatial variability of soil properties are compared. The first approach is based on the random field theory and involves the Cholesky decomposition and Monte Carlo simulation (MCS) in its solution. The second approach is a simplified procedure based on the variance reduction technique and realized through the first-order reliability method (FORM). In the simplified approach, the spatial correlation of the spatial averages of tip resistance and side resistance of the drilled shaft is also considered in the reliability analysis. The reliability analyses of drilled shafts based on serviceability limit state (SLS) are performed at various levels of spatial variability of soil properties. The results of the analyses show that the two probabilistic approaches yield comparable failure probabilities. However, the simplified approach significantly reduces the computational effort and can be easily implemented in an Excel spreadsheet and thus is recommended for the engineering practice. This research also shows that neglecting spatial variability of soil properties can lead to either an overestimation or an underestimation of the SLS failure probability, depending on the load on the drilled shaft. The importance of considering the spatial variability in the reliability-based design of drilled shafts is thus highlighted through the work presented in this paper.
Effect of Spatial Variability on the Reliability-Based Design of Drilled Shafts
In this paper, two probabilistic approaches for implementing the reliability-based design of drilled shafts considering the spatial variability of soil properties are compared. The first approach is based on the random field theory and involves the Cholesky decomposition and Monte Carlo simulation (MCS) in its solution. The second approach is a simplified procedure based on the variance reduction technique and realized through the first-order reliability method (FORM). In the simplified approach, the spatial correlation of the spatial averages of tip resistance and side resistance of the drilled shaft is also considered in the reliability analysis. The reliability analyses of drilled shafts based on serviceability limit state (SLS) are performed at various levels of spatial variability of soil properties. The results of the analyses show that the two probabilistic approaches yield comparable failure probabilities. However, the simplified approach significantly reduces the computational effort and can be easily implemented in an Excel spreadsheet and thus is recommended for the engineering practice. This research also shows that neglecting spatial variability of soil properties can lead to either an overestimation or an underestimation of the SLS failure probability, depending on the load on the drilled shaft. The importance of considering the spatial variability in the reliability-based design of drilled shafts is thus highlighted through the work presented in this paper.
Effect of Spatial Variability on the Reliability-Based Design of Drilled Shafts
Luo, Zhe (author) / Wang, Lei (author) / Khoshnevisan, Sara (author) / Juang, C. Hsein (author)
Geo-Congress 2014 ; 2014 ; Atlanta, Georgia
Geo-Congress 2014 Technical Papers ; 3274-3282
2014-02-24
Conference paper
Electronic Resource
English
Effect of Spatial Variability on the Reliability-Based Design of Drilled Shafts
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