Stability of active trapdoors in axisymmetry

Trapdoor stability has been widely studied by many researchers in the field of tunneling engineering. A general question being frequently asked is that why most sinkholes have a near-perfect circular shape on the ground surface. This could be possibly explained by the current numerical study using finite element limit analysis under axisymmetric condition, where upper and lower bound solutions of active circular trapdoors are determined. The failure study of sinkholes and the associated failure mechanisms in this paper are for non-homogeneous clay with a linear increase of strength with depth under various cover depth ratios and dimensionless strength gradients. A design equation for predicting the stability solutions is also developed based on the novel three dimensional solutions using axisymmetry

Seismic Analysis of Earth Slope Using a Novel Sequential Hybrid Optimization Algorithm

One of the most important topics in geotechnical engineering is seismic analysis of the earth slope. In this study, a pseudo-static limit equilibrium approach is applied for the slope stability evaluation under earthquake loading based on the Morgenstern–Price method for the general shape of the slip surface. In this approach, the minimum factor of safety corresponding to the critical failure surface should be investigated and it is a complex optimization problem. This paper proposed an effective sequential hybrid optimization algorithm based on the tunicate swarm algorithm (TSA) and pattern search (PS) for seismic slope stability analysis. The proposed method employs the global search ability of TSA and the local search ability of PS. The performance of the new CTSA-PS algorithm is investigated using a set of benchmark test functions and the results are compared with the standard TSA and some other methods from the literature. In addition, two case studies from the literature are considered to evaluate the efficiency of the proposed CTSA-PS for seismic slope stability analysis. The numerical investigations show that the new approach may provide better optimal solutions and outperform previous methods

Bearing Capacity of Cylindrical Caissons in Cohesive‑Frictional Soils Using Axisymmetric Finite Element Limit Analysis

This paper investigates the use of stability factors for estimating the ultimate bearing pressures on cylindrical caissons in cohesive-frictional soils. Rigorous upper and lower bound limit analyses with finite elements in axisymmetric (AX) condition are used for a series of numerical studies. The bearing capacity factors (Nc0, Nq0 and Nγ0) for a surface circular footing are firstly revisited. This is followed by a study on the effect of caisson’s embedded depth ratio (L/D). A comprehensive set of depth factors (Fcd, Fqd and Fγd) is then reported as a function of caisson’s embedded depth ratio (L/D) and soil internal friction angle (ϕ). The obtained results are compared with published solutions in the literature. Several examples are given to validate the principal of superposition as well as to illustrate on how to use the produced factors to estimate the ultimate bearing pressures on cylindrical caissons in cohesive-frictional soils. The study should be of great interests to practitioners

Stability Charts for Closely Spaced Strip Footings on Hoek–Brown Rock Mass

Footings are constructed closely to each other in mountainous rock areas and the determination of closely spaced bearing capacity footings on rock masses has become an important topic of recent research. The primary aim of this paper is to determine an efficiency factor, just like in the design of a pile group, that can be used to evaluate the bearing capacity of closely spaced footings on Hoek–Brown mass. The advanced finite element limit analysis of upper and lower bound theorems is used to study the stability of two and multiple interfering footings using the Hoek–Brown parameters such as GSI (geological strength index) and mi (Hoek–Brown yield parameter). This study found that the efficiency factor is influenced by three dimensionless parameters including GSI, mi, and S/B. Failure mechanisms of the problems are also investigated, and stability charts and tables produced for practical uses. Overall, these results broadly support the common understanding of the two key parameters GSI and mi in the HB failure criterion. As a result of these investigations, suggestions were identified for future research

Finite Element Analysis to Estimate Bearing Capacity of Strip Footing in Coastal Sandy Soils in Bengkulu City, Indonesia

This study presents results of bearing capacity analysis for strip footing in coastal sandy soils. Three sites located at coastal area are investigated. The site investigation and laboratory tests are conducted to obtain soil properties. Variations on depth and width of strip footing are considered. Finite element analysis is conducted to observe failure mechanism and bearing capacity of strip footing. Several results such as relationship between ultimate bearing capacity and foundation dimensions, factor of safety, displacement, and failure mechanism are discussed. The comparison between finite element results and exact solutions is also presented. The results show that variations of dimension tend to influence the bearing capacity and failure mechanism. The results also shows that finite element result is generally consistent with the exact solution. The results states that the footing dimension of 1.1. m embedded at 1.0 m below ground surface as the suitable strip footing in the study area. This study can also benefit local engineers designing strip footing for the coastal sandy soils

Multiscale soft computing-based model of shear strength of steel fibre-reinforced concrete beams

Concrete is weak in tension, so steel fibres are added to the concrete members to increase shear capability. The shear capacity of steel fibre-reinforced concrete (SFRC) beams is crucial when building reinforced concrete structures. Creating a precise equation to determine the shear resistance of SFRC beams is challenging since many factors can influence the shear capacity of these beams. In addition, the precision available equations to predict the shear capacity are examined. The current research aims to examine the available equations and propose novel and more accurate model to predict the shear capacity of SFRC beams. An innovative evolutionary polynomial regression analysis (EPR- MOGA) is utilized to propose the new equation. The proposed equation offered improved prediction and increased accuracy compared to available equations, where it scored a lower mean absolute error (MAE) and root mean square error (RMSE), a mean (μ) close to the optimum value of 1.0 and a higher coefficient of determination (R 2) when a comparison with literature was conducted. Therefore, the new equation can be employed to assure more resilient and optimized design calculations due to their improved performance.</p

Sinkhole stability in elliptical cavity under collapse and blowout conditions

Road subsidence and sinkhole failures due to shallow cavities formed by defective water main have increased in recent decades and become one of the important research topics in geotechnical engineering. The present paper numerically studies the stability and its associated failure mechanism of ellipse-shaped cavity above defective water mains using the finite element limit analysis technique. For a wide range of geometrical parameters, the pressure ratio method is used to formulate the stability solutions in both blowout and collapse scenarios. Even though there is no published solution for elliptical cavities under blowout failure conditions, the obtained numerical results are compared with available circular solutions. Several conclusions are drawn based on the failure mechanism study of the various ellipse shape transformations in this study, whilst design charts and equations proposed for practical uses

Application of soft computing in predicting the compressive strength of self-compacted concrete containing recyclable aggregate

Self-compacting concrete (SCC) is a type of concrete known for its environmental benefits and improved workability. In this study, data-driven approaches were used to anticipate the compressive strength (CS) of self-compacting concrete (SCC) containing recycled plastic aggregates (RPA). A database of 400 experimental data sets was used to assess the capabilities of Multi-Objective Genetic Algorithm Evolutionary Polynomial Regression (MOGA-EPR) and Gene Expression Programming (GEP). The analysis results indicated that the proposed equations provided more accurate CS predictions than traditional approaches such as the Linear Regression model (LRM). The proposed equations achieved lower mean absolute error (MAE) and root mean square error (RMSE) values, a mean close to the optimum value (1.0), and a higher coefficient of determination (R2) than the LRM. As such, the proposed approaches can be utilized to obtain more reliable design calculations and better predictions of CS in SCC incorporating RPA