Stratified slopes, numerical and empirical stability analysis

Urbanisation means that many natural slopes in and around cities are often subjected to cuts resulting in dramatic changes in the geometry of slope faces mostly by increasing slope angle which could lead to failures with catastrophic consequences. As most natural slopes are of nonhomogeneous layered nature, understanding the stability behaviour of such slopes will be of utmost importance. The current practice in analysing slopes of complicated nature, geometrically and materially, is mostly to apply simplifications sacrificing accuracy leading to use of large factors of safety, which could undermine analytical and economic feasibility of projects. In this research limit-equilibrium and finite element methods are used, respectively by OASYS Slope and PLAXIS 2D, to empirically and numerically model and analyse geometrically non-homogeneous stratified slopes with the aim of understanding the effects of non-homogeneity of geometry and materials on stability under various inclination angles of slope face. The analysis included determination of factors of safety as well as a sensitivity analysis looking into the combined effects of contributing parameters

A surrogate model for simulation–optimization of aquifer systems subjected to seawater intrusion

This study presents the application of Evolutionary Polynomial Regression (EPR) as a pattern recognition system to predicate the behavior of nonlinear and computationally complex aquifer systems subjected to seawater intrusion (SWI). The developed EPR models are integrated with a multi objective genetic algorithm to examine the efficiency of different arrangements of hydraulic barriers in controlling SWI. The objective of the optimization is to minimize the economic and environmental costs. The developed EPR model is trained and tested for different control scenarios, on sets of data including different pumping patterns as inputs and the corresponding set of numerically calculated outputs. The results are compared with those obtained by direct linking of the numerical simulation model with the optimization tool. The results of the two above-mentioned simulation–optimization (S/O) strategies are in excellent agreement. Three management scenarios are considered involving simultaneous use of abstraction and recharge to control SWI. Minimization of cost of the management process and the salinity levels in the aquifer are the two objective functions used for evaluating the efficiency of each management scenario. By considering the effects of the unsaturated zone, a subsurface pond is used to collect the water and artificially recharge the aquifer. The distinguished feature of EPR emerges in its application as the metamodel in the S/O process where it significantly reduces the overall computational complexity and time. The results also suggest that the application of other sources of water such as treated waste water (TWW) and/or storm water, coupled with continuous abstraction of brackish water and its desalination and use is the most cost effective method to control SWI. A sensitivity analysis is conducted to investigate the effects of different external sources of recharge water and different recovery ratios of desalination plant on the optimal results

The effect of cut-off wall angle on seepage and uplift pressure under dams

Seepage under dams can result in high uplift pressure experienced usually under the downstream of the dam which may lead to instability and potentially the failure of the dam. Cut-off walls are the primary solution to minimise the effects caused by the flow of water, as they extend the flow path which results in decreasing seepage, as well as uplift pressure and exit gradient. (Rice & Duncan, 2010) This study aims to research how designing a cut-off wall at an angle under a concrete dam increases its efficiency. The angles will vary from 0° to 180°, progressively increasing at an interval of 30°. Following that, two walls will be designed originating from the same point at the nose of the dam, as well as another design where the walls are under both ends of the structure. The modal analysis will be completed using the finite element geotechnical software – PLAXIS 2D, as it has proved to be extremely precise in discharge analysis specifically (Galavi, 2010). A typical impervious concrete dam will be designed in the program in a uniform soil profile with the only variable being the angle of the cut-off wall and its originating point. This is done to put the attention simply on the discharge value that is obtained from the software. The feasibility of the construction will always be taken into account, as this study intends to complete research by taking a realistic and economic approach. The results show that seepage is smallest when the cut-off wall is positioned at a 60° angle, as in this position water has to travel the furthest distance compared to the other configurations. In terms of uplift pressure, the dam experienced the least pressure when the wall is at 120°. As seepage and uplift pressure are the two main factors playing significant roles in the stability of dams – two combined configurations were introduced into the model in order to minimise both values; one being the addition of the 60° and 120° angle walls originating at both ends of the dam, and the other where the two formerly mentioned walls originated from the same point (the heel of the dam). The configuration where the two walls are constructed under the heel and the toe show a significant decrease in seepage, as well as uplift pressure at the toe. When the two walls are both constructed originating from the same point (heel) – seepage is determined to be lower compared to when only one wall is considered, however a significant reduction in uplift pressure is not present. When taking all data into account, the most feasible, economical and practical solution to decreasing seepage and uplift pressure considerably appears to be the arrangement where a 60° cut-off wall is constructed at the heel of the dam and 120 ° wall at the toe of the dam

A comparative analysis of the stability of homogeneous and non-homogeneous soil slopes subject to various surcharge loading conditions

Slope stability is a topic of great importance within the scope of civil engineering, this study investigates the differences between homogeneous and non-homogenous soil slopes when various surcharge loading conditions are applied. To analyse slope stability the finite element method is used, this method uses the shear strength reduction method. This method gradually reduces the cohesion and friction angle of the soil until failure occurs in the model. Typically, the limit equilibrium method is used by civil engineers, which splits the model into slices to identify the failure mechanisms and the factor of safety. However, as the software improves, and the accuracy of analysis increases, finite element analysis will become the more commonly used method [1, 2]. In this study 6 different models are used in the analysis, three homogenous soil slopes and three nonhomogenous soil slopes to aid in the analysis, the soil properties were obtained from [3]. Each model was subject to surcharge loading, which was incrementally increased until failure occurred, recording the factor of safety at each point. The results gathered suggest that point loads caused failure in models to occur much quicker than surcharge loading from a uniformly distributed load, however, the failure area is much smaller. The comparison of homogenous and non-homogenous soil slopes shows that stability is dependent on three key properties including cohesion, unit weight, and friction angle, with the properties of the soil slope influencing the maximum surcharge loading that can be applied to a model. The results indicate that homogenous soils can withstand higher surcharge loading conditions compared to that of nonhomogenous soil slopes, except for homogenous models consisting of silty sand

Numerical implementation of EPR-based material models in finite element analysis

In this paper a novel approach based on evolutionary polynomial regression (EPR) is presented to develop constitutive models of materials. Stress–strain data are used to train EPR and develop EPR-based material models. It is shown that it is possible to construct the material stiffness (Jacobian) matrix using partial derivatives of the developed EPR models. The EPR-based Jacobian matrix is implemented in finite element (FE) model and two boundary value problems are used to verify the proposed EPR-based FE methodology. It is shown that the EPR-FE model can be successfully employed to analyse structural problems with both linear and non-linear material behaviour

Analysis of behaviour of soils under cyclic loading using EPR-based finite element method

In this paper, a new approach is presented for modelling of behaviour of soils in finite element analysis under cyclic loading. This involves development of a unified approach to modelling of complex materials using evolutionary polynomial regression (EPR) and its implementation in the finite element method. EPR is a data mining technique that generates a clear and structured representation of the system being studied. The main advantage of an EPR-based constitutive model (EPRCM) over conventional models is that it provides the optimum structure and parameter of the material model directly from raw experimental (or field) data. The development and validation of the method will be presented followed by the application to study of behaviour of soils under cyclic loading. The results of the analyses will be compared with those obtained from standard finite element analysis using conventional constitutive models. It will be shown that the EPR-based models offer an effective and unified approach to modelling of materials with complex behaviour in finite element analysis of boundary value problems

A new approach for prediction of the stability of soil and rock slopes

Purpose – Analysis of stability of slopes has been the subject of many research works in the past decades. Prediction of stability of slopes is of great importance in many civil engineering structures including earth dams, retaining walls and trenches. There are several parameters that contribute to the stability of slopes. This paper aims to present a new approach, based on evolutionary polynomial regression (EPR), for analysis of stability of soil and rock slopes. Design/methodology/approach – EPR is a data-driven method based on evolutionary computing, aimed to search for polynomial structures representing a system. In this technique, a combination of the genetic algorithm and the least square method is used to find feasible structures and the appropriate constants for those structures. Findings – EPR models are developed and validated using results from sets of field data on the stability status of soil and rock slopes. The developed models are used to predict the factor of safety of slopes against failure for conditions not used in the model building process. The results show that the proposed approach is very effective and robust in modelling the behaviour of slopes and provides a unified approach to analysis of slope stability problems. It is also shown that the models can predict various aspects of behaviour of slopes correctly. Originality/value – In this paper a new evolutionary data mining approach is presented for the analysis of stability of soil and rock slopes. The new approach overcomes the shortcomings of the traditional and artificial neural network-based methods presented in the literature for the analysis of slopes. EPR provides a viable tool to find a structured representation of the system,which allows the user to gain additional information on how the system performs

An evolutionary approach to modelling compaction characteristics of soils

An Evolutionary approach is used for prediction of maximum dry density (MDD) and optimum moisture content (OMC) as functions of some physical properties of soil. Evolutionary polynomial regression (EPR) is a data-driven method based on evolutionary computing aimed to search for polynomial structures representing a system. In this technique, a combination of the genetic algorithm (GA) and the least square method is used to find feasible structures and the appropriate parameters of those structures. EPR models are developed based on results from a series of classification and compaction tests from literature. Standard Proctor tests conducted on soils made of four components, bentonite, limestone dust, sand, and gravel, mixed in different proportions. The results of the EPR model predictions are compared with those of a neural network model, a correlation equation from literature and the experimental data. Comparison of the results shows that the proposed models are highly accurate and robust in predicting compaction characteristics of soils. Results from sensitivity analysis indicate that the models trained from experimental data have been able to capture the physical relationships between soil parameters. The proposed models are also able to represent the degree to which individual contributing parameters affect the maximum dry density and optimum moisture content