Probabilistic analysis of site-specific load-displacement behaviour of cement-fly ash-gravel piles

Wu, Xing Zheng; Xin, Jun-Xia

doi:10.1016/j.sandf.2019.07.003

Cited by 14 publications

(7 citation statements)

References 42 publications

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“…The correlation coefficient between 𝑝 1 and 𝑝 2 is set with −0.65. 20 If the best-fit marginal distribution type is known, the normal copula function is used to calculate the results. The single standard deviation ellipse is obtained by Equation ( 2), whereas the 𝛽= 1 configuration is defined by Equations ( 11) and ( 12) for given a unit reliability index.…”

Section: Variablementioning

confidence: 99%

“…The load−displacement data of a CFG pile composite foundation is used to evaluate their bearing reliability. The test site is located in Daxing District in Beijing, China 20 and the test was performed by Beijing Construction Engineering Quality First Testing Institute Co. Ltd. 21 In terms of the technical specifications for building foundation pile testing, 22 a total of 32 composite foundations have been tested on this site, and the measured pressure−displacement curves are shown in Figure 6A. The performance function or limit state equation used to evaluate the bearing resistance of composite foundation is defined as:…”

Section: Two Variables-cement Fly-ash Gravel (Cfg) Pile Composite Fou...mentioning

confidence: 99%

“…The best‐fit distribution type and the corresponding parameters are listed in Table 1. The correlation coefficient between p 1 and p 2 is set with −0.65 20 …”

Section: Illustrative Examplesmentioning

confidence: 99%

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Solving the geometric reliability index for a case involving multivariate random variables in the original physical space

Wang

2023

Quality & Reliability Eng

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An effective interpretation of the complex reliability theory will promote its application in engineering practice. Based on an algorithm for solving the geometric reliability index for cases involving two or three random variables in the original physical space, an advanced algorithm for multivariate random variables is further developed by using a hypersphere model and inverse Nataf transformation. The main components of the algorithm include the definition of limit state surface, the construction of a hypersphere model, the determination of probability density iso‐contour points, the identification of limit state of these points, and the definition of an actual reliability index. Several typical practical problems associated with two to five variables are analyzed, and the results are compared with those obtained using the first‐order reliability method (FORM) and the copula‐based sampling method (CBSM), thus validating the accuracy of the proposed algorithm. With the help of the powerful and open‐source R language platform, the visualization of a reliability index in low dimensions and the solvability in high dimensions are implemented, which makes the interpretation of reliability theory more intuitive.

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Section: Variablementioning

confidence: 99%

Section: Two Variables-cement Fly-ash Gravel (Cfg) Pile Composite Fou...mentioning

confidence: 99%

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Solving the geometric reliability index for a case involving multivariate random variables in the original physical space

Wang

2023

Quality & Reliability Eng

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“…Therefore, the effect of temperature and heart exchange soil and CFG pile behaviour studied by Nguyen and Phan [18]. According to Wu et al [19], the CFG pile ground improvement treatment is very effective on a field test on different ground improvement techniques. It is also uhelpful for an important highway project by Nguyen and Phan [18]; Wu et al [19]; Hashemi et al [20], and Hamidi and Lajevardi [21].…”

mentioning

confidence: 99%

“…According to Wu et al [19], the CFG pile ground improvement treatment is very effective on a field test on different ground improvement techniques. It is also uhelpful for an important highway project by Nguyen and Phan [18]; Wu et al [19]; Hashemi et al [20], and Hamidi and Lajevardi [21]. It has been a less vertical settlement and minimum lateral deformation than other ground improvement tests.…”

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confidence: 99%

Numerical Analysis to Study Lateral Behavior of Cement Fly Ash Gravel Piles under the Soft Soil

Umravia

Solanki

2022

IJE

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Cement Fly ash and Gravel Piles are modern soil improvement techniques widely used in China for infrastructure development. It significantly impacts the fundamental characteristics of load-carrying capacities and deformation. The cement fly ash and gravel (CFG) piles are located on highways, railway embankments, essential projects, and problematic soil. These are often subjected to high risk of external load like flooding, seismic, etc. In such a case, foundation design can be governed by a required lateral resistance. The present study is based on the deformation behaviour of a CFG pile subjected to axial, lateral, and combined loading in soft clay. Numerical analysis using Plaxis 3D on a CFG pile with various influencing parameters soil condition, diameters, length, length to diameter ratio, and pile head loading condition to observe its effect. Overall, the pile study found variations in initial stress level, pile type, and pile head constraint. Still, these were minor compared to the impact of soil behaviour and mobility. The soil models varied stiffness and strength properties. The effects originating from the boundary conditions used were responsible for significantly decreasing lateral resistance for inner CFG piles under the active and passive loading.

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Basics of Probability Theory

Zhang,

Xiao,

et al. 2023

Geotechnical Reliability Analysis

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Probabilistic analysis of site-specific load-displacement behaviour of cement-fly ash-gravel piles

Cited by 14 publications

References 42 publications

Solving the geometric reliability index for a case involving multivariate random variables in the original physical space

Solving the geometric reliability index for a case involving multivariate random variables in the original physical space

Numerical Analysis to Study Lateral Behavior of Cement Fly Ash Gravel Piles under the Soft Soil

Basics of Probability Theory

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