Reliability analysis of foundation settlement by stochastic response surface and random finite element method

Johari, A.; Sabzi, A.

doi:10.24200/sci.2017.4169

Cited by 8 publications

(5 citation statements)

References 28 publications

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“…The spatial variability of modulus, cohesion, and internal friction angle was mainly considered in this chapter [12]. About 30 calculation conditions were designed as shown in Table 2.I n each condition, the random fields of E, c, and φ were simulated by five kinds of autocorrelation functions.…”

Section: Randomness Analysismentioning

confidence: 99%

“…Lo and Leung [11] used Latin hypercube sampling with dependence to simulate the random field, which was coupled with polynomial chaos expansion to approximate the probability density function of model response, and applied it to the reliability analysis of strip foundation and slope. Johari [12] presented a reliability-based analysis of strip-footing settlement by stochastic finite-element method and combined with random finite-element method to improve computational efficiency.…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic Settlement Analysis of Granular Soft Soil Foundation in Southern China Considering Spatial Variability

Huang¹,

Huang²,

Yu³

2018

Granularity in Materials Science

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In this chapter, the method of combining the theory of random field and numerical analysis was used to systematically analyze the settlement probability of the soft soil foundation in the south of China, considering the effect of spatial variability of soil parameters. Based on the midpoint discretization and Cholesky decomposition, the cross-correlated non-Gaussian random field of cohesion and internal friction angle was constructed, which had considered the cross-correlation, and a single parameter random field of modulus was also constructed. The Monte-Carlo stochastic finite element program for two-dimensional foundation probabilistic settlement was developed in APDL language. The influence of spatial variability of soil parameters on probability foundation settlement was studied. The results indicate that the foundation settlement increases with the increase of coefficient variation and correlation distance. Modulus is the most important parameter for foundation settlement. The settlement of foundation is more sensitive to the correlation distance in vertical direction. Based on exponential square autocorrelation function, the continuity of random fields is obviously better, and the foundation settlement is larger. On the contrary, the fluctuation of random fields is larger, and the foundation settlement is smaller with single exponential autocorrelation function.

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Section: Randomness Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Probabilistic Settlement Analysis of Granular Soft Soil Foundation in Southern China Considering Spatial Variability

Huang¹,

Huang²,

Yu³

2018

Granularity in Materials Science

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“…In previous studies, many aspects that may bring uncertainty to the site response have been tested: (i) input information such as shear wave velocity, material damping, modulus reduction, input ground motion, shear elastic modulus, unit density, damping ratio, and the thickness of the soil deposit 4–10 , (ii) in situ geophysical measurements of shear wave velocity 11,12 , (iii) the effect of multiple numerical simulation codes, including numerical code, analysis method, nonlinear constitutive model 13–15 . These studies show that the uncertainty of seismic response may come from all aspects of the whole analysis process, of which shear wave velocity is the dominant factor and its influence is more significant than any other parameters.…”

Section: Introductionmentioning

confidence: 99%

Dynamic site response analysis in the face of uncertainty–an approach based on response surface method

Liu

Juang

Chen

et al. 2021

Num Anal Meth Geomechanics

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Although advanced modeling techniques such as the finite element method (FEM) have been used successfully in dynamic site response analysis, the high computational expense has hindered the incorporation of input parameter uncertainty in such analysis. Thus, when the variation of the peak ground acceleration (PGA) at the ground surface, which is the outcome of the site response analysis, has to be evaluated in the face of uncertainty, a surrogate model such as Response Surface Method (RSM) model is often used in lieu of the FEM model. In this paper, the RSM surrogate model was implemented in the context of seismic site response analysis to evaluate the variation (or uncertainty) of the PGA due to the propagation of input parameter uncertainty. The engineering implication of the variation of the surface PGA is significant as this knowledge is required for such tasks as reliability analysis of soil liquefaction and probabilistic seismic risk analysis. To derive the RSM model specifically for a site response analysis, a parametric study of the dynamic site responses using FEM code ABAQUS with the modified Davidenkov soil constitutive model implemented as a user‐defined material subroutine is first conducted. The input parameters, including the soil profile, soil properties, and input ground motion, in a typical dynamic site response analysis are then characterized and screened for their suitability to be included in the RSM model. For a given site response problem in the face of uncertainty, representative “samples” are taken for site response analysis using ABAQUS, and the analyses are carried out and finally the response surface is constructed using the outcomes of the ABAQUS numerical experimentations. The accuracy of the developed RSM model is then validated using the results of ABAQUS on cases not used in the development of the RSM model. Once the RSM model is deemed satisfactory, the reliability‐based formulation for evaluating the mean and standard deviation of the surface PGA is established. Example is provided to illustrate the RSM approach for dynamic site response analysis in the face of input parameter uncertainty.

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“…For the same number of piles, the change in piles distribution over the raft area was a slight effect on the piled raft average settlement, while it had a considerable effect on the piled raft differential settlement. Johari et al (2017) carried reliability analysis of seismic ultimate bearing capacity of strip footing by slip lines method coupled with random field theory. They compared probability density functions of seismic and static bearing capacities to each other.…”

Section: Introductionmentioning

confidence: 99%

“…The predicted probability density function (PDF) of the seismic bearing capacity by slip line method is verified, with those of the Terzaghi equation and Monte Carlo simulation (MCs). Johari and Sabzi (2017) presented reliability-based analysis of strip footing settlement by stochastic finite element method (SFEM). The stochastic response surface method (SRSM) and random finite element method (RFEM) are used as two formulation of SFEM.…”

Section: Introductionmentioning

confidence: 99%

Assessing the effect of governing parameters of bearing capacity determination of small piled rafts on clay soil

Mali

Singh

2021

Arab J Geosci

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In the present study, a small piled raft foundation has been simulated numerically through PLAXIS 3-D software. The objective of this study was to investigate the effect of governing parameters such as pile length, pile spacing, pile diameter, and number of piles on the settlement and load-bearing behavior of piled raft, so as to achieve the optimum design for small piled raft configurations. An optimized design of a piled raft is defined as a design with allowable center and differential settlements and satisfactory bearing behavior for a given raft geometry and loading. The results indicated that, with increase in pile length, pile spacing, pile diameter, and number of piles, both the center settlement ratio and differential settlement ratio decreased. The load-bearing capacity of piled raft increased with increase in pile length, pile spacing, pile diameter, and number of piles. Furthermore, the percentage load carried by the piles increased as the pile length, pile spacing, pile diameter, and number of piles increased. The bending moment and shear force in corner pile are noted to be more, and they decreased towards the center pile. With increase in pile length, the maximum raft bending moment decreased, whereas the maximum shear force in the raft increased. Further, with increase in pile spacing, pile diameter, and number of piles, the maximum bending moment and maximum shear force in the raft increased. The optimum parameters for the piled raft foundation can be selected efficiently with the consideration of maximum bending moment and maximum shear force while designing the piled raft foundation. Thus, the results of this study can be used as guidelines for achieving optimum design for small piled raft foundation.

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Reliability analysis of foundation settlement by stochastic response surface and random finite element method

Cited by 8 publications

References 28 publications

Probabilistic Settlement Analysis of Granular Soft Soil Foundation in Southern China Considering Spatial Variability

Probabilistic Settlement Analysis of Granular Soft Soil Foundation in Southern China Considering Spatial Variability

Dynamic site response analysis in the face of uncertainty–an approach based on response surface method

Assessing the effect of governing parameters of bearing capacity determination of small piled rafts on clay soil

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