This study employs the random finite element method (RFEM) to analyze the wall deflection caused by excavation. The RFEM combined random fields of material properties with the FEM through the Monte Carlo simulation. A...This study employs the random finite element method (RFEM) to analyze the wall deflection caused by excavation. The RFEM combined random fields of material properties with the FEM through the Monte Carlo simulation. A well-documented excavation case history is employed to evaluate the influence of uncertainty of analysis parameters. This study shows that RFEM can provide reasonable estimations of the exceedance probability of wall deflection caused by excavation, and has the potential to be a useful tool to account for the uncertainties of material and model parameters in the numerical analysis.展开更多
Natural soil variability is a well-known issue in geotechnical design,although not frequently managed in practice.When subsoil must be characterized in terms of mechanical properties for infrastructure design,random f...Natural soil variability is a well-known issue in geotechnical design,although not frequently managed in practice.When subsoil must be characterized in terms of mechanical properties for infrastructure design,random finite element method(RFEM)can be effectively adopted for shallow foundation design to gain a twofold purpose:(1)understanding how much the bearing capacity is affected by the spatial variability structure of soils,and(2)optimisation of the foundation dimension(i.e.width B).The present study focuses on calculating the bearing capacity of shallow foundations by RFEM in terms of undrained and drained conditions.The spatial variability structure of soil is characterized by the autocorrelation function and the scale of fluctuation(δ).The latter has been derived by geostatistical tools such as the ordinary Kriging(OK)approach based on 182 cone penetration tests(CPTs)performed in the alluvial plain in Bologna Province,Italy.Results show that the increase of the B/δratio not only reduces the bearing capacity uncertainty but also increases its mean value under drained conditions.Conversely,under the undrained condition,the autocorrelation function strongly affects the mean values of bearing capacity.Therefore,the authors advise caution when selecting the autocorrelation function model for describing the soil spatial variability structure and point out that undrained conditions are more affected by soil variability compared to the drained ones.展开更多
The cement mixing (CM) pile is a common method of improving soft offshore ground. The strength growth of CM piles under complex conditions is affected by many factors, especially the cement and moisture contents, and ...The cement mixing (CM) pile is a common method of improving soft offshore ground. The strength growth of CM piles under complex conditions is affected by many factors, especially the cement and moisture contents, and shows significant uncertainty. To investigate the stochasticity of the early strength of CM piles and its impact on the displacement and stability of a seawall, a series of laboratory tests and numerical analyses were carried out in this study. Vane shear tests were conducted on the cement-solidified soil to determine the relationships between the undrained shear strength s_(u) of the cement soil curing in the seawater and the cement content a_(c), as well as the in situ soil moisture content w. It can be inferred that the 24 h undrained shear strength follows a normal distribution. A numerical model considering the random CM pile strength was established to investigate the deformation of the seawall. Due to the uncertainty of CM pile strength, the displacement of the seawall demonstrates a certain discreteness. The decrease of the mean undrained shear strength of CM piles causes a corresponding increase in the average displacement of the seawall. When the mean strength of CM piles is lower than a certain threshold, there is a risk of instability. Furthermore, the heterogeneity of the strength within an individual CM pile also has an impact on seawall displacement. Attention should be paid to the uncertainty of CM pile strength to control displacement and stability.展开更多
基金Project (No. NSC 99-2221-E-146-004) supported by the National Science Council
文摘This study employs the random finite element method (RFEM) to analyze the wall deflection caused by excavation. The RFEM combined random fields of material properties with the FEM through the Monte Carlo simulation. A well-documented excavation case history is employed to evaluate the influence of uncertainty of analysis parameters. This study shows that RFEM can provide reasonable estimations of the exceedance probability of wall deflection caused by excavation, and has the potential to be a useful tool to account for the uncertainties of material and model parameters in the numerical analysis.
文摘Natural soil variability is a well-known issue in geotechnical design,although not frequently managed in practice.When subsoil must be characterized in terms of mechanical properties for infrastructure design,random finite element method(RFEM)can be effectively adopted for shallow foundation design to gain a twofold purpose:(1)understanding how much the bearing capacity is affected by the spatial variability structure of soils,and(2)optimisation of the foundation dimension(i.e.width B).The present study focuses on calculating the bearing capacity of shallow foundations by RFEM in terms of undrained and drained conditions.The spatial variability structure of soil is characterized by the autocorrelation function and the scale of fluctuation(δ).The latter has been derived by geostatistical tools such as the ordinary Kriging(OK)approach based on 182 cone penetration tests(CPTs)performed in the alluvial plain in Bologna Province,Italy.Results show that the increase of the B/δratio not only reduces the bearing capacity uncertainty but also increases its mean value under drained conditions.Conversely,under the undrained condition,the autocorrelation function strongly affects the mean values of bearing capacity.Therefore,the authors advise caution when selecting the autocorrelation function model for describing the soil spatial variability structure and point out that undrained conditions are more affected by soil variability compared to the drained ones.
基金supported by the Finance Science and Technology Project of Hainan Province(No.ZDKJ202019)the Key Research and Development Program of Zhejiang Province(No.2021C03014)the Natural Science Foundation of Zhejiang Province(No.LR22E080005),China.
文摘The cement mixing (CM) pile is a common method of improving soft offshore ground. The strength growth of CM piles under complex conditions is affected by many factors, especially the cement and moisture contents, and shows significant uncertainty. To investigate the stochasticity of the early strength of CM piles and its impact on the displacement and stability of a seawall, a series of laboratory tests and numerical analyses were carried out in this study. Vane shear tests were conducted on the cement-solidified soil to determine the relationships between the undrained shear strength s_(u) of the cement soil curing in the seawater and the cement content a_(c), as well as the in situ soil moisture content w. It can be inferred that the 24 h undrained shear strength follows a normal distribution. A numerical model considering the random CM pile strength was established to investigate the deformation of the seawall. Due to the uncertainty of CM pile strength, the displacement of the seawall demonstrates a certain discreteness. The decrease of the mean undrained shear strength of CM piles causes a corresponding increase in the average displacement of the seawall. When the mean strength of CM piles is lower than a certain threshold, there is a risk of instability. Furthermore, the heterogeneity of the strength within an individual CM pile also has an impact on seawall displacement. Attention should be paid to the uncertainty of CM pile strength to control displacement and stability.
