Effects of soil spatial variability on structural reliability assessment in excavations

Luo, Zhe; Di, Honggui; Kamalzare, Mehrad; Li, Yixiang

doi:10.1016/j.undsp.2018.10.004

Cited by 28 publications

(7 citation statements)

References 18 publications

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“…Wong et al [11] summarized the supporting effect of different foundation pit retaining structures. Luo et al [12,13] proposed a reliability-based design method for the retaining structure of the foundation pit that considers spatial variability of the soil. Tan et al [14] proposed that rapid excavation, timely support, timely pouring of floors, and sectional construction are critical for deformation control of the foundation pit.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the Axial Force Compensation and Deformation Control Effect of Servo Steel Struts in a Deep Foundation Pit Excavation in Soft Clay

Guo

Zhou

et al. 2019

Advances in Civil Engineering

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This study presents a comparative analysis of the deformation control effect of the hydraulic servo steel struts and ordinary steel struts of a foundation pit based on the measured axial force of the steel struts, lateral wall deflection, and ground surface settlement due to pit excavation. The results indicate that ordinary steel struts installed via axial preloading exhibit a disadvantageous axial force loss with a maximum value equal to 86.7% of the axial preloading force. When compared with ordinary steel struts, the hydraulic servo steel strut exhibits a superior supporting effect. The hydraulic servo steel strut adjusts the axial force in real time based on the deformation of the retaining structure and the axial force of the struts. Thus, the ratio of maximum lateral deflection to the excavation depth of a deep foundation pit in soft soil is less than 0.3%. Concrete struts undergo unsupported exposure during the excavation process, leading to sharply increasing deformation of the retaining structure. Therefore, regarding a foundation pit with strict requirements for deformation control, the use of hydraulic servo steel struts rather than concrete struts is recommended.

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Section: Introductionmentioning

confidence: 99%

Investigation of the Axial Force Compensation and Deformation Control Effect of Servo Steel Struts in a Deep Foundation Pit Excavation in Soft Clay

Guo

Zhou

et al. 2019

Advances in Civil Engineering

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“…Besides the data-interpretation approach, the forward model is another important factor in inverse analyses. The commonly used forward models in probabilistic inverse analyses are the empirical models 5,17 and the surrogate models trained from numerical simulation data. 4,16 For ease of computation, numerical simulations (such as FEMs) are seldom directly used in probabilistic inverse analyses but used for constructing an efficient surrogate model, which is then run repeatedly during the inverse analysis.…”

Section: Introductionmentioning

confidence: 99%

A bi‐fidelity inverse analysis method for deep excavations considering three‐dimensional effects

Tao,

Pan,

Sun

et al. 2024

Num Anal Meth Geomechanics

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Inverse analysis methods are commonly used in braced excavations for improved deformation predictions. This paper proposes a bi‐fidelity ensemble randomized maximum likelihood (BF‐EnRML) method for efficient inverse analyses of deep excavations considering the three‐dimensional effects. The bi‐fidelity (BF) model is developed by the low‐fidelity model (i.e., two‐dimensional finite element model, 2D FEM) and the high‐fidelity model (i.e., 3D FEM) for a balance between efficiency and accuracy. A large number of 2D FEMs are first used to explore the relationship between soil parameters and wall deflections. A few 3D FEMs are then performed to calibrate the discrepancy between 2D‐3D deflections caused by the inability of 2D FEM to consider the three‐dimensional effects. The constructed BF model serves as the forward model in inverse analysis. The soil parameters are updated by incorporating the monitoring data based on EnRML and further used to predict wall deflections in later stages. A hypothetical excavation and a real project are studied to evaluate the performance of the proposed method. The results show that the BF model can provide wall deflection predictions close to those calculated from 3D FEM while using a computational cost of 2D FEM. The BF‐EnRML method can efficiently update the soil parameters and improve the wall deflection predictions. Moreover, factors affecting the accuracy of the BF model are studied, including the number of required 3D FEMs, the distance from the evaluated wall section to the excavation corner, the number of data points along the wall depth, and the number of excavation stages.

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“…The purpose of reliability analysis is to estimate the failure probability of a structural system during normal operation under given conditions. At present, reliability analysis has received widespread attention in engineering applications, such as mechanical systems, 6 infrastructure engineering, 7 automobiles, 8 and industrial robots. 9 Estimating failure probability (P f ) based on a mechanical model is the key to slope reliability analysis.…”

Section: Introductionmentioning

confidence: 99%

Copula‐based importance sampling method for efficient slope reliability analysis

Zhou

Xiao

Jiang

et al. 2023

Num Anal Meth Geomechanics

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Efficient slope reliability analysis that accounts for the interdependencies of random variables is challenging. In this study, an efficient reliability method is proposed based on importance sampling (IS) and copulas. First, the IS method based on the design point is introduced to construct the marginal IS density. Copulas are subsequently adopted to capture the interdependencies and establish both the initial joint distributions and the joint IS densities of random variable pairs. The IS algorithm is modified to consider the dependencies through not only the estimation of the probability distribution but also random sampling. Finally, a framework of the copula‐based IS method is constructed. The applicability, accuracy, efficiency, and robustness of the proposed method were validated by a classical slope case. The results showed that with the proposed method, slope reliability could be efficiently assessed with a relatively high accuracy. The dependencies of the variables significantly affected the IS and final slope reliability, whereas the IS density had a significantly lower effect. The proposed method combines the advantages of IS and copulas well. Interdependencies of the variables can be properly characterized during sampling. Moreover, the proposed method was shown to be robust regardless of the system failure probability level. It can be further applied to improve the random finite element method in the future.

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Effects of soil spatial variability on structural reliability assessment in excavations

Cited by 28 publications

References 18 publications

Investigation of the Axial Force Compensation and Deformation Control Effect of Servo Steel Struts in a Deep Foundation Pit Excavation in Soft Clay

Investigation of the Axial Force Compensation and Deformation Control Effect of Servo Steel Struts in a Deep Foundation Pit Excavation in Soft Clay

A bi‐fidelity inverse analysis method for deep excavations considering three‐dimensional effects

Copula‐based importance sampling method for efficient slope reliability analysis

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