Search

This study aimed to emphasize the significance of spatial variability in soil strength parameters on the behavior of nailed walls, highlighting the necessity of probabilistic design approaches. The investigation involved a 7.2-m nailed wall reinforced with five nails, simulated using the local average subdivision random field theory combined with the limit equilibrium method and the FEM, known as the random limit equilibrium method (RLEM) and the random finite-element method (RFEM) approaches. Initially, the wall stability was evaluated by RLEM using 10,000 Latin hypercube sampling realizations. The wall was globally stable among all samples for a correlation length equal to its height (7.2 m). The wall behavior, associated displacements, moments, wall shear forces, nail axial forces, and ground settlements were examined using RFEM. The RFEM analysis reveals that different random fields influence the maximum displacement (Hmax), maximum moment (Mmax), and maximum shear force (Vmax) experienced by the wall. The cumulative distribution function plots were generated for the wall critical parameters, including Hmax, Mmax, and Vmax. Leveraging the simple weighted averaging and ordered weighted averaging techniques, different combinations of Hmax, Mmax, and Vmax were assessed with varying weight assumptions. This allowed us to identify critical random field realizations and estimate the level of risk using a newly introduced parameter, the decision index. Finally, the effect of different correlation lengths (isotropic and anisotropic) for two different coefficients of variation of soil strength parameters on the distribution of Hmax, Mmax, and Vmax was studied. The findings highlight the importance of considering the spatial variability of soil properties to achieve a reliable design of nailed walls. [ABSTRACT FROM AUTHOR]

The main objective of this study is to evaluate the ultimate seismic bearing capacity of a shallow strip footing resting on a frictional soil stratum containing a weak intervening layer. The majority of the studies throughout the literature pertain to the static loading condition. The previous seismic analyses have also been devoted to the studies on the bearing capacity of shallow strip footings resting on a two-layered soil. The influence of weak middle layer on the pseudo-static seismic bearing capacity of shallow foundations is the main focus of the present study. To determine the seismic bearing capacity, the limit equilibrium method (LEM) was combined with the pseudo-static seismic loading approach. Bearing capacity was defined by a single equivalent coefficient which combines the contributions of cohesion, surcharge and soil weight. A two-wedge failure surface, known as the Coulomb failure mechanism, was adopted to model the slip lines in each layer to calculate the seismic bearing capacity of the overlying shallow strip footing. The Particle Swarm Optimization (PSO) algorithm was invoked to seek the optimal bearing capacity value under different strength and loading conditions. In order to verify the validity of the presented formulations, the results were compared with some Finite Elements Method (FEM) analyses available in literature. Furthermore, the influence of the embedment depth, thickness, and strength of the weak inter-layer on the seismic bearing capacity of the shallow footing is investigated in the presence of different seismic loading arrangements. The results of this study could be very helpful in the seismic analysis and design of shallow foundations overlying a soil medium containing a weak layer of various strengths. [ABSTRACT FROM AUTHOR]

The 2D random finite element method and the one-dimensional and 2D random limit equilibrium method are used to investigate the influence of spatial variability of soil strength parameters on the probability of failure of simple soil slopes with cohesive undrained shear strength. The combined influence of spatial variability of soil properties and cross-correlation between undrained soil strength and unit weight on the computed probability of failure is explored. The paper identifies conditions where numerical outcomes are similar and where they are not. The limitations of each analysis method are described and implications to analysis and design are identified. Abbreviations:FEM: finite element method; LEM: limit equilibrium method; RFEM: random finite element method; RLEM: random limit equilibrium method [ABSTRACT FROM PUBLISHER]

Probabilistic slope stability analyses of simple geosynthetic reinforced soil slopes were carried out using the shear strength reduction method in combination with the finite element method (FEM). An existing open-source FEM code was modified to include bar elements to model horizontal layers of geosynthetic reinforcement. Analysis results using the modified code (mFEM) demonstrate that large reductions in probability of failure can be realized by adding geosynthetic reinforcement layers to constructed slopes. The modified code was also used to investigate the effect of variability of soil friction angle on probabilistic outcomes for constructed unreinforced and reinforced purely frictional soil slopes. [ABSTRACT FROM AUTHOR]

• Precise estimation of the support system parameters of a subway station. • Developing a stochastic multi-objective optimization model using NSGA-III. • Estimating the risk of uncertainties in c and ϕ by CVaR. • Ranking all optimal solutions using The ELECTRE model. The process of designing the support system of a subway station using a concrete arch pre-supporting system (CAPS) construction method includes an estimation of design variables based on intuition and experience. However, this process may often lead to controversial and economically unfavorable designs. In this regard, developing an optimization model to determine design variables (support system parameters) is necessary. In this study, a stochastic optimization model is developed to determine the support system parameters of a subway station constructed using CAPS. To estimate the risk of uncertainties of the soil properties, the concept of conditional value at risk (CVaR) is used. A Python script is programmed in cooperation with a 2D Finite Element Method (FEM) software to provide the dataset. Then, the results are applied to prepare multi-layer perceptron (MLP) models, which are subsequently used as meta-models and linked to a reference-point-based non-dominated sorting genetic algorithm III (NSGA-III). It should be noted that the selection of the NSGA-III algorithm was based on comparing its performance with a few other meta-heuristic algorithms such as NSGA-II, MOPSO, and MOMBIII considering metrics such as hypervolume (HV), inverted generational distance (IGD), spread, and pure diversity (PD). Finally, all optimal solutions are ranked using the ELECTRE multi-criteria decision-making method. Various weighting scenarios for the objectives are considered to evaluate the importance of the selected design criteria. The results of the numerical modeling confirm that the proposed algorithm can provide worthwhile information for a logical decision about the support system parameters of a subway station. Thus, the outcome of this study is to achieve an appropriate and economical design by minimizing four following objectives: the risk of instability, risk of the maximum surface settlement, risk of the maximum displacement throughout the station structure, and the concreting volume. The presented algorithm could also alter the prioritization of design goals based on the project's sensitivity and the designer's judgment. On the other hand, by considering the uncertainty in soil parameters, the optimal parameters of the support system are determined more accurately in comparison with an assumption of homogenous soil. Therefore, the main contribution of this article to the design of a subway station constructed by the CAPS method is to increase the accuracy of the design of support system parameters by considering the risk of uncertainties in soil parameters, the importance of the project, and goals of the designer. In this way; the overly conservative designs in practice would be avoided. [ABSTRACT FROM AUTHOR]