Dr Majid Nazem

The use of cement as a curing agent has been widely adopted in soft soil engineering to increase the strength of soft soil. The cemented soil is gradually exposed to the air and in a natural environment becomes unsaturated. Unconfined compressive strength (UCS) of the unsaturated cemented soils is a key parameter for assessing their strength behaviour. UCS determination of unsaturated cemented soils by using laboratory methods is a complex, time-consuming, and expensive procedure due to the difficulty in suction control. This study aims to model the UCS of unsaturated cemented Wenzhou clay, i.e., capture the nonlinear relations between UCS and its influential variables including cement content (%), dry density (g/cm3) and suction (MPa) for the first time by using machine learning approach. Toward this aim, three advanced computational frameworks are developed based on hybrid evolutionary approaches in which evolutionary optimisation algorithms including genetic algorithm (GA), particle swarm optimisation (PSO) and imperialist competitive algorithm (ICA) are hybridised with artificial neural network (ANN). Results show that developed models have a great ability to mimic the nonlinear relationships between UCS and its influential variables and PSO-ANN presents the best performance among three models on the training dataset with R2=0.9888, RMSE=0.129 and VAF=97.742, and testing dataset with R2=0.9412, RMSE=0.237 and VAF=90.414. To facilitate engineering application, an engineering database for Wenzhou soft clay at different cement ratios (up to 11%), suctions (up to 300 MPa) and dry densities (1¿1.5 g/cm3) is built by using the developed PSO-ANN model.

Thermal conductivity is a specific thermal property of soil which controls the exchange of thermal energy. If predicted accurately, the thermal conductivity of soil has a significant effect on geothermal applications. Since the thermal conductivity is influenced by multiple variables including soil type and mineralogy, dry density, and water content, its precise prediction becomes a challenging problem. In this study, novel computational approaches including hybridisation of two metaheuristic optimisation algorithms, i.e. firefly algorithm (FF) and improved firefly algorithm (IFF), with conventional machine learning techniques including extreme learning machine (ELM), adaptive neuro-fuzzy interface system (ANFIS) and artificial neural network (ANN), are proposed to predict the thermal conductivity of unsaturated soils. FF and IFF are used to optimise the internal parameters of the ELM, ANFIS and ANN. These six hybrid models are applied to the dataset of 257 soil cases considering six influential variables for predicting the thermal conductivity of unsaturated soils. Several performance parameters are used to verify the predictive performance and generalisation capability of the developed hybrid models. The obtained results from the computational process confirmed that ELM-IFF attained the best predictive performance with a coefficient of determination = 0.9615, variance account for = 96.06%, root mean square error = 0.0428, and mean absolute error = 0.0316 on the testing dataset (validation phase). The results of the models are also visualised and analysed through different approaches using Taylor diagrams, regression error characteristic curves and area under curve scores, rank analysis and a novel method called accuracy matrix. It was found that all the proposed hybrid models have a great ability to be considered as alternatives for empirical relevant models. The developed ELM-IFF model can be employed in the initial stages of any engineering projects for fast determination of thermal conductivity.

In this paper, we present a novel framework for solving boundary and initial-value problems involving multiphase granular soils under monotonic, cyclic, and dynamic loads. To achieve this, a constitutive model was developed using the concept of loading surface that allows the development of a stress integration scheme with less algorithmic complexity compared to its counterparts developed for the models that involve a yield or bounding surface. The developed model was implemented in a fully coupled framework to tackle several challenging issues in the numerical modelling of granular soils, including induced anisotropy and the response in scenarios including elevated stress levels, cyclic loading, during wetting and drying reversals, and under impact loads. Several numerical examples are presented, providing verification of the approach, and demonstrating the capabilities of the proposed solution framework.

Mesh distortion is one of the main drawbacks of the Finite Element method when employed to analyse problems with relatively large deformations. The entanglement of elements caused by large deformations in a finite element mesh may lead to spontaneous termination of the analysis or inaccurate results. The Arbitrary Lagrangian-Eulerian method is a robust numerical technique widely used for problems involving large deformations. In this study four remeshing techniques including the Spring Analogy method, the Spring Analogy Elastic Hardening method, the Elastic Analys method and the Radial Basis Functions method are presented for analysing geotechnical problems within the framework of the Arbitrary Lagrangian-Eulerian strategy. The performance of these methods in reducing mesh distortion is comprehensively studied. In addition, several mesh quality metrics specifically designed for the 6-noded triangular elements are used to assess these mesh refinement methods. The performance of these mesh refienemnt techniques is investigated by solving a few geotechnical problems including the soil resistance under a rigid strip footing subjected to large deformations, the soil response due to loading on the edge of a vertical cut, dynamic penetration of a free-falling penetrometer into a layer of soil, and dynamic indentation of a sphere into a soil layer.

Tight carbonate reservoirs appear to be heterogeneous due to the patchy production of various digenetic properties. Consequently, the permeability calculation of tight rocks is costly, and only a finite number of core plugs in any single reservoir can be estimated. Hence, in the present study, a novel hybrid model constructed by combination of the improved version of the Harris Hawks optimisation (HHO), i.e., IHHO, and extreme learning machine (ELM) is proposed to predict the permeability of tight carbonates using limited number of input variables. The proposed IHHO employs a mutation mechanism to avoid trapping in local optima by increasing the search capabilities. Subsequently, ELM-IHHO, a novel metaheuristic ELM-based algorithm, was developed to predict the permeability of tight carbonates. Experimental results show that the proposed ELM-IHHO attained the most accurate prediction with R2 = 0.9254 and RMSE = 0.0619 in the testing phase. The result of the proposed model is significantly better than those obtained from other ELM-based hybrid models developed with particle swarm optimisation, genetic algorithm, and slime mould algorithm. The results also illustrate that the proposed ELM-IHHO model outperforms the other benchmark model, such as back-propagation neural nets, support vector regression, random forest, and group method of data handling in predicting the permeability of tight carbonates.

It is a problematic task to perform petro-physical property prediction of carbonate reservoir rocks in most cases, specifically for permeability prediction since a carbonate rock most commonly contains grains of heterogeneous size distributions. Consequently, the permeability calculation of tight rocks in laboratories is costly and very time-consuming. Therefore, this study aims to tackle this issue by developing novel hybrid models based on combination of the modified version of the equilibrium optimizer (EO), i.e., MEO, and two conventional machine learning algorithms, namely extreme learning machine (ELM) and artificial neural network (ANN). The MEO employs a mutation mechanism in order to avoid trapping in local optima of EO by increasing the search capabilities. In this study, ELM-MEO and ANN-MEO, novel metaheuristic ELM-based and ANN-based algorithms, were constructed to predict the permeability of tight carbonates. In addition, ANN, ELM, RF, RVM and MARS combined with particle swarm optimization and genetic programming algorithm have a better insight into the performances for preferably predicting the permeability carbonates. The results illustrate that the proposed ELM-MEO model with R2 = 0.9323, RMSE = 0.0612 and MAE = 0.0442 in training stage and R2 = 0.8743, RMSE = 0.0806 and MAE = 0.0660 in testing stage, outperformed other ELM-based and ANN-based metaheuristic models in predicting the permeability of tight carbonates at all levels.

The development of a numerical procedure for the finite element analysis of anchors dynamically penetrating into saturated soils is outlined, highlighting its unique features and capabilities. The mechanical behaviour of saturated porous media is predicted using mixture theory. An algorithm is developed for frictional contact in terms of effective normal stress. The contact formulation is based on a mortar segment-to-segment scheme, which considers the interpolation functions of the contact elements to be of order N, thus overcoming a numerical deficiency of the so-called node-to-segment (NTS) contact algorithm. The nonlinear behaviour of the solid constituent is captured by the Modified Cam Clay soil model. The soil constitutive model is also adapted so as to incorporate the dependence of clay strength on strain rate. An appropriate energy-absorbing boundary is used to eliminate possible wave reflections from the artificial mesh boundaries. To illustrate the use of the proposed computational scheme, simulations of dynamically penetrating anchors are conducted. Results are presented and discussed for the installation phase followed by 'setup', i.e., pore pressure dissipation and soil consolidation. The results, in particular, reveal the effects of strain rate on the generation of excess pore pressure, bearing resistance and frictional forces. The setup analyses also illustrate the pattern in which pore pressures are dissipated within the soil domain after installation. Hole closure behind a dynamic projectile is also illustrated by an example.

The aim of this paper is to address a number of significant challenges in the analysis of multiphase unsaturated soils when subjected to both static and dynamic loading. These challenges include the non-linear behaviour of the solid skeleton of the soil as well as the means by which the unsaturated nature of the multi-phase soil is dealt with. A review of some fundamental issues in partially saturated soils as well as the governing equations are presented and then the application of the generalised-. a algorithm for time integration of the global equations of motion for unsaturated soils is demonstrated. Solutions to these equations obtained by the finite element method are validated by recently presented analytical solutions. A description of the selected constitutive model and its integration is also presented, together with a strategy to verify the numerical implementation. Finally, solutions for the classic problem of static loading of a rigid footing resting on a partially saturated (three-phase) soil and a fully saturated (two-phase) soil are presented.

A finite element algorithm for frictionless contact problems in a two-phase saturated porous medium, considering finite deformation and inertia effects, has been formulated and implemented in a finite element programme. The mechanical behaviour of the saturated porous medium is predicted using mixture theory, which models the dynamic advection of fluids through a fully saturated porous solid matrix. The resulting mixed formulation predicts all field variables including the solid displacement, pore fluid pressure and Darcy velocity of the pore fluid. The contact constraints arising from the requirement for continuity of the contact traction, as well as the fluid flow across the contact interface, are enforced using a penalty approach that is regularised with an augmented Lagrangian method. The contact formulation is based on a mortar segment-to-segment scheme that allows the interpolation functions of the contact elements to be of order N. The main thrust of this paper is therefore how to deal with contact interfaces in problems that involve both dynamics and consolidation and possibly large deformations of porous media. The numerical algorithm is first verified using several illustrative examples. This algorithm is then employed to solve a pipe-seabed interaction problem, involving large deformations and dynamic effects, and the results of the analysis are also compared with those obtained using a node-to-segment contact algorithm. The results of this study indicate that the proposed method is able to solve the highly nonlinear problem of dynamic soil-structure interaction when coupled with pore water pressures and Darcy velocity.

Dynamic penetrometers have been used for offshore oil and gas industry applications such as pipeline feasibility studies and anchoring systems, and military applications including naval mine countermeasures and terminal ballistic studies. The main challenge of using dynamic penetrometers is the interpretation of their test results in order to deduce the mechanical properties of the penetrated soil via empirical or theoretical relations. Recently, a robust numerical method based on the Arbitrary Lagrangian-Eulerian (ALE) technique has been developed for analysing dynamic penetration problems and used to investigate a smooth penetrometer free falling into a uniform layer of clayey soil. Numerical as well as experimental results indicate that the penetration characteristics, including the impact energy, total time, and total depth of penetration, depend on the mechanical properties of the soil including its stiffness and strength parameters as well as the geometry of the penetrometer and its initial impact energy. In this study, the ALE method is employed to study the effect of shear strength increasing with depth (a common condition of seabed deposits) on the penetration characteristics of a free falling penetrometer. Conducting more than two thousand numerical simulations has shown that there is an approximate quadratic relation between the final embedment depth of a FFP penetrating into a non-uniform clay soil and the combined kinetic energy on contact with the soil and subsequent loss in potential energy of the penetrometer.

In this paper high-order triangular elements are implemented in the framework of the Arbitrary Lagrangian-Eulerian method for the analysis of large strain consolidation problems in geomechanics. The theory of consolidation, as well as details of the high-order elements, including cubic (10-noded), quartic (15-noded), quantic (21-noded) and sextic (28- noded) elements are discussed. The accuracy and the efficiency of high-order elements in the analysis of consolidation problems are demonstrated conducting a small deformation analysis of the soil under a strip footing as well as a large deformation analysis of a vertical cut subjected to a surcharge loading. Based on the numerical results, it is shown that high-order elements not only improve the accuracy of solution but can also significantly decrease the required computational time. It is also demonstrated that assuming identical order for displacement shape functions and the pore water pressure shape functions does not affect the stability of the time-marching analysis of consolidation nor the accuracy of the numerical predictions.

Geotechnical applications often involve large displacements of structural elements, such as penetrometers or footings, in soil. Three numerical analysis approaches capable of accounting for large deformations are investigated here: the implicit remeshing and interpolation technique by small strain (RITSS), an efficient Arbitrary Lagrangian-Eulerian (EALE) implicit method and the Coupled Eulerian-Lagrangian (CEL) approach available as part of commercial software. The theoretical basis and implementation of the methods are discussed before their relative performance is evaluated through four benchmark cases covering static, dynamic and coupled problems in geotechnical engineering. Available established analytical and numerical results are also provided for comparison purpose. The advantages and limitation of the different approaches are highlighted. The RITSS and EALE predict comparable results in all cases, demonstrating the robustness of both in-house codes. Employing implicit integration scheme, RITSS and EALE have stable convergence although their computational efficiency may be low for high-speed problems. The CEL is commercially available, but user expertise on element size, critical step time and critical velocity for quasi-static analysis is required. Additionally, mesh-independency is not satisfactorily achieved in the CEL analysis for the dynamic case.

This paper investigates the application of high-order elements within the framework of the arbitrary Lagrangian-Eulerian method for the analysis of elastoplastic problems involving large deformations. The governing equations of the method as well as its important aspects such as the nodal stress recovery and the remapping of state variables are discussed. The efficiency and accuracy of 6-, 10-, 15-, and 21-noded triangular elements are compared for the analysis of two geotechnical engineering problems, namely, the behavior of an undrained layer of soil under a strip footing subjected to large deformations and the soil behavior in a biaxial test. The use of high-order elements is shown to increase the accuracy of the numerical results and to significantly decrease the computational time required to achieve a specific level of accuracy. For problems considered in this study, the 21-noded elements outperform other triangular elements.

This paper provides an overview of the work of the Australian Research Council-funded Centre for Geotechnical Science and Engineering on free falling projectiles that have applications as seabed characterisation tools and as anchoring systems for floating facilities. These projectiles are released in water and dynamically embed into the seabed through the kinetic energy they gain during freefall. The high penetration velocity, which can be up to 25 m/s at impact with the seabed, induces shear strain rates in the soil that are up to eight orders of magnitude higher than in a typical laboratory test. The difficulty in quantifying the soil strength at these very high strain rates, together with hydrodynamic aspects including pressure drag and potential water entrainment along the projectile-soil interface, complicates assessment of the penetration response. A large database of centrifuge and field data has been collated by the Centre and is used in this paper to quantify embedment potential and to examine the merit of a simple analytical framework that captures the dynamic response of free-falling projectiles. Aspects of the dynamic embedment process that cannot be predicted by the analytical framework, including potential hole closure during installation and pore pressure generation are investigated in finite element analyses that model the dynamic penetration of projectiles in soil. Example results from these analyses are provided.

In this paper high-order triangular elements are implemented in the framework of the Arbitrary Lagrangian-Eulerian method for the analysis of large strain coupled consolidation problems in geomechanics. The theory of coupled consolidation, as well as details of the high-order elements, including quadratic (6-noded), cubic (10-noded), quartic (15-noded) and quantic (21-noded) elements, are discussed. The accuracy and the efficiency of high-order elements in the analysis of undrained problems are presented by solving two classical geomechanics problems. These include the bearing capacity of soil under a footing and the large deformation analysis of a vertical cut subjected to a surcharge loading. Based on the numerical results, it is shown that high-order elements not only improve the accuracy of the solution, but can also significantly decrease the required computational time.

In this paper we study the performance of the discrete element method (DEM) and the extended finite element method (XFEM) modelling the crack initiation, propagation and coalescence in fractured rock masses. Firstly, the crack propagation in a rock sample with single closed and open flaws and subjected to an uniaxial compression is simulated by the DEM and XFEM. The results obtained by the two methods are then compared with the experimental results reported by Park and Bobet (2009). Under an uniaxial compression load, two types of cracks are observed including the tensile or wing cracks, and the shear or secondary cracks. The results obtained by the DEM are in good agreement with the experimental results, viz., both wing and shear cracks are accurately modelled. The XFEM, on the other hand, can predict the tensile (wing) cracks, but fails to model the shear cracks. In second part of this study we consider the analysis of fracture propagation and coalescence in rock masses containing two open or closed flaws. The results predicted by the DEM and XFEM are then compared with experimental test results. Coalescence is produced by the linkage of two flaws and a combination of wing and secondary cracks. In the crack propagation and coalescence problem, the DEM is able to predict all cracks involved in rock fracturing, such as the wing and secondary cracks, as well as the crack linkage between two adjacent flaws and their subsequent coalescence. However, the XFEM results only represent the wing cracks, and the method fails to predict the shear cracks. Finally, the effect of filling materials in open flaws on the crack propagation is investigated. The results indicate that the initiation and propagation of cracks and their coalescence in a material containing open flaws significantly change when the flaws are filled with a weak material. © 2014 Elsevier B.V. All rights reserved.

In rail infrastructure maintenance management systems, Track Degradation Index (TDI) is considered as a representative of quality of rail tracks. This index is usually developed based on the deviation rate or standard deviation of track geometry parameters. In this regard, prediction of future TDI is an important task as it can be employed to determine when and where maintenance and renewal activities must be deployed. In this study, a track geometry data set from Melbourne tram network has been used as the case study and gauge deviation parameter is selected as the main parameter to develop TDI. For prediction of the future TDI, Random Forests (RF) model as a Machine Learning (ML) model is used to predict the future TDI of the data set. Since TDI is a continuous variable, Random Forests Regression (RFR) model is applied. In this study, RF model has added two algorithms to the basic Decision Trees (DT) model including bagging and random subspace method. These algorithms can reduce the overfitting problem and over-focus on special features. Based on the results of this study, adjusted R2 value of the proposed prediction model is 0.93, which demonstrates that the model has the satisfying performance in predicting the TDI.

© 2018 ATRF, Commonwealth of Australia. All rights reserved. In rail infrastructure maintenance management systems, Track Degradation Index (TDI) is considered as a representative of quality of rail tracks. This index is usually developed based on the deviation rate or standard deviation of track geometry parameters. In this regard, prediction of future TDI is an important task as it can be employed to determine when and where maintenance and renewal activities must be deployed. In this study, a track geometry data set from Melbourne tram network has been used as the case study and gauge deviation parameter is selected as the main parameter to develop TDI. For prediction of the future TDI, Random Forests (RF) model as a Machine Learning (ML) model is used to predict the future TDI of the data set. Since TDI is a continuous variable, Random Forests Regression (RFR) model is applied. In this study, RF model has added two algorithms to the basic Decision Trees (DT) model including bagging and random subspace method. These algorithms can reduce the overfitting problem and over-focus on special features. Based on the results of this study, adjusted R2 value of the proposed prediction model is 0.93, which demonstrates that the model has the satisfying performance in predicting the TDI.

© 2018 ATRF, Commonwealth of Australia. All rights reserved. In rail infrastructure maintenance management systems, Track Degradation Index (TDI) is considered as a representative of quality of rail tracks. This index is usually developed based on the deviation rate or standard deviation of track geometry parameters. In this regard, prediction of future TDI is an important task as it can be employed to determine when and where maintenance and renewal activities must be deployed. In this study, a track geometry data set from Melbourne tram network has been used as the case study and gauge deviation parameter is selected as the main parameter to develop TDI. For prediction of the future TDI, Random Forests (RF) model as a Machine Learning (ML) model is used to predict the future TDI of the data set. Since TDI is a continuous variable, Random Forests Regression (RFR) model is applied. In this study, RF model has added two algorithms to the basic Decision Trees (DT) model including bagging and random subspace method. These algorithms can reduce the overfitting problem and over-focus on special features. Based on the results of this study, adjusted R2 value of the proposed prediction model is 0.93, which demonstrates that the model has the satisfying performance in predicting the TDI.

Nowadays, tram as an accessible and convenient mode of public transport is implemented and used in different cities. Due to high frequency of accelerations and decelerations along their routes and sharing the route with other vehicles, the rate of degradation of tram tracks (light rail) is different from the degradation rate of train tracks (heavy rail). In this paper, track gauge deviation as an indicator of irregularities on the rail-wheel contact surface is used for developing the track degradation model. Data set used in this study includes the curve sections of Melbourne tram network and divided into repaired and unrepaired segments. For data analysis more than 13 km of curved tracks are examined. Annual tonnage, previous gauge deviation and track structural properties like track surface, rail support, rail profile and gauge deviation are considered as the influencing variables on the future gauge deviation. Two different models including a regression model and an Artificial Neural Networks (ANN) model have been developed for predicting tram track gauge deviation. According to the results, the performances of the regression models are not very different from the ANN models. The determination coefficients of the selected models are approximately 0.8 and higher.

© 2017 ATRF, Commonwealth of Australia. All rights reserved. Nowadays, tram as an accessible and convenient mode of public transport is implemented and used in different cities. Due to high frequency of accelerations and decelerations along their routes and sharing the route with other vehicles, the rate of degradation of tram tracks (light rail) is different from the degradation rate of train tracks (heavy rail). In this paper, track gauge deviation as an indicator of irregularities on the rail-wheel contact surface is used for developing the track degradation model. Data set used in this study includes the curve sections of Melbourne tram network and divided into repaired and unrepaired segments. For data analysis more than 13 km of curved tracks are examined. Annual tonnage, previous gauge deviation and track structural properties like track surface, rail support, rail profile and gauge deviation are considered as the influencing variables on the future gauge deviation. Two different models including a regression model and an Artificial Neural Networks (ANN) model have been developed for predicting tram track gauge deviation. According to the results, the performances of the regression models are not very different from the ANN models. The determination coefficients of the selected models are approximately 0.8 and higher.

© 2017 ATRF, Commonwealth of Australia. All rights reserved. Nowadays, tram as an accessible and convenient mode of public transport is implemented and used in different cities. Due to high frequency of accelerations and decelerations along their routes and sharing the route with other vehicles, the rate of degradation of tram tracks (light rail) is different from the degradation rate of train tracks (heavy rail). In this paper, track gauge deviation as an indicator of irregularities on the rail-wheel contact surface is used for developing the track degradation model. Data set used in this study includes the curve sections of Melbourne tram network and divided into repaired and unrepaired segments. For data analysis more than 13 km of curved tracks are examined. Annual tonnage, previous gauge deviation and track structural properties like track surface, rail support, rail profile and gauge deviation are considered as the influencing variables on the future gauge deviation. Two different models including a regression model and an Artificial Neural Networks (ANN) model have been developed for predicting tram track gauge deviation. According to the results, the performances of the regression models are not very different from the ANN models. The determination coefficients of the selected models are approximately 0.8 and higher.

There exist many problems in the offshore geotechnical setting which necessitate a dynamic analysis or a consolidation analysis. In recent years literature on this topic has been dominated by the application of Finite Element Methods to solving such problems and addressing the inherent shortcomings associated with their use. These issues include, but are not limited to, the occurrence of mesh distortion in problems involving large deformations and the inability to adequately capture discontinuities. The intrinsic nature of meshfree methods, however, makes them a more appropriate means of solving offshore geotechnical problems. This study presents a robust Maximum-Entropy Meshless method for nonlinear analysis of offshore problems in which the effect of time-dependent behaviour cannot be ignored. The Generalised-a time integration scheme and the Backward-Euler method are respectively employed for dynamic analysis and coupled analysis of such problems. The applicability of this meshless method is presented by studying the undrained soil behaviour under a circular footing subjected to dynamic loading as well as static loading.

The main aim of this study is to apply a robust time integration technique for simulating the behaviour of unsaturated soils subjected to dynamic loads. The governing equations of the three soil phases and their interactions are derived based on the mass conservation law, linear momentum balance and energy conservation of each phase in an isothermal environment. In addition, a number of experimental equations are employed to represent the hydraulic conductivity and the drainage characteristics of the soil, such as the suction-saturation relationship and the dependency of the hydraulic conductivity on suction. The global system of equations is then solved by using an implicit time-stepping algorithm based on the Generalised-a integration scheme. The accuracy of the numerical model and the finite element code is verified by comparing the numerical results with results obtained by an analytical solution. © 2015 Taylor & Francis Group, London.

This study outlines the development of a computational scheme which accounts for large deformation dynamic behaviour of saturated porous media and models soil-structure interaction using a high-order frictional contact algorithm. The numerical scheme is employed to analyse a dynamic coupled problem of pipeline-seabed interaction in two steps, including the simulation of the dynamic embedment process as well as the subsequent consolidation stage. The analysis considers a frictional interface between the pipe and the soil which is normally ignored in most analyses due to numerical difficulties. The nonlinear behaviour of the solid constituent is captured by the Modified Cam Clay soil model, allowing the incorporation of shear-induced pore water pressures during the embedment process. The results of this study indicate that the proposed method is able to solve the highly nonlinear problem of dynamic soil-pipe interaction coupled with pore water pressures and Darcy velocity. The results also show that a dynamic approach is necessary for coupled problems of pipe-seabed interaction involving very fast loading. © 2015 Taylor & Francis Group, London.

Dynamic compaction is known as one of the most cost-effective soil improvement techniques. In this method the soil at the ground surface or at a relatively deep depth is compacted by repeatedly dropping heavy weights on the ground. Since its introduction, dynamic compaction has exhibited its versatility and simplicity of use in different types of civil engineering projects, including building structures, container terminals, highways, airports, dockyards, and harbours. However, despite the abundance of experimental data and field observation reports, few numerical approaches have been established in the literature to effectively deal with soil behaviour under dynamic compaction. This is mainly due to the dependence of soil dynamic response on variations in the moisture content. Therefore, to achieve a comprehensive understanding of dynamic compaction the soil should be modelled as a three-phase porous medium. The presence of a non-wetting and a wetting phase, together with the existence of inertia forces in each phase, makes the solution of the coupled dynamic system computationally demanding. Moreover, large deformations often take place during dynamic compaction; hence the infinitesimal strain theory cannot be employed for higher impact loads. In this paper a finite element approach is introduced to numerically simulate the problem of dynamic compaction under the framework of unsaturated soil mechanics. The governing equations are derived based upon the overall momentum balance of the mixture, the mass balance of the liquid phase, and the mass balance of the gas phase. Phase changes and chemical reactions are not considered. Among other important parameters, the effect of the degree of saturation on the soil response will be addressed.

The dynamic penetration of anchors into the seabed is an important problem in offshore geomechanics and one of the most challenging for geotechnical analysts. Complications due to the nonlinear material response of the soil, the large deformations caused by the insertion of the object, and the changing boundary conditions at the contact between the soil and the anchors must be taken into account. Moreover, the presence of a pore fluid, and the pressure that it may exert, requires a fully coupled displacement-pore pressure analysis. Recent work has facilitated the modelling of the dynamic penetration of objects into soil. The finite element method is one of the most commonly used techniques for tackling problems of soil penetration because the resulting solutions satisfy the equation of dynamic equilibrium and the method can incorporate sophisticated soil models as well as complex boundary conditions. This study discusses a number of challenging aspects of the numerical simulation of dynamically embedded anchors, particularly torpedo anchors, and presents a robust analysis strategy for such problems. This technique is based on the Arbitrary Lagrangian-Eulerian method and rigorously incorporates displacements, velocities, and accelerations of the solid phase along with the pore pressure and velocities of the fluid phase.

Numerical simulation of collapse of tunnels in weak rocks is one of the challenging problems in rock mechanics. Collapse can impose technical and financial difficulties during the construction of underground excavations. This phenomenon, particularly in shallow excavations, may lead to propagation of a caved zone toward the surface and formation of chimney subsidence. Chimney subsidence has numerous catastrophic consequences such as the adverse environmental impacts and damage to surface structures in vicinity of excavations. Due to the importance of subsidence in civil engineering, the main goal of this study is to propose an appropriate method for preventing the formation of subsidence in shallow tunnels in weak rocks. The Dolaei road tunnel is investigated as a case study, where a large chimney subsidence has occurred. The geology of the area and the geostructural characteristics of the rock mass surrounding the tunnel are briefly reviewed in this paper. Two-dimensional as well as three-dimensional numerical simulations are conducted to study the tunnel stability. Moreover, the effects of staged excavation and pre-supporting method on controlling the ground movements are studied. Outcomes of this study indicate that employing forepoling and staged excavation can be a practical remedy to control the ground movements and prevent the formation of chimney subsidence.

This paper addresses the application of high-order elements in the analysis of soil penetration problems, particularly those involving inertia forces and large deformations. Among others, 15-node triangular elements are formulated within an Arbitrary Lagrangian-Eulerian finite element method. Preliminary studies indicate that high-order elements can significantly decrease the analysis time without significant loss of accuracy. © (2014) Trans Tech Publications, Switzerland.

This paper presents the development of a numerical framework based on the finite element method and its application in the analysis of torpedo anchors. The procedure is based on a mixture theory for the dynamic behaviour of saturated porous media. The nonlinear behaviour of the solid phase of soil is represented by the Modified Cam Clay material model and the interface between the soil and the structure is modelled by a mortar segment-to-segment frictional contact method. An Arbitrary Lagrangian-Eulerian (ALE) method is adopted to avoid mesh distortion throughout the numerical simulation. The generalised-a method is utilised to integrate the governing equations of motion in the time domain. Results obtained from the installation phase of a torpedo anchor reveal that the anchor decelerates at a constant rate during most of its penetration. Analysis results show a typical distribution of excess pore-water pressure during free falling installation, having higher magnitudes at the face and lower magnitudes along the shaft. The computational results for the setup phase indicate that for soil elements located within a radial distance of approximately one diameter from the centreline of the torpedo, 90% of consolidation takes place in a few days after installation, depending on the value of soil permeability.

Ground subsidence due to mining is a very complicated geomechanics phenomenon, particularly in the longwall mining method. Due to the adverse consequences of subsidence on surface structures, facilities, and environment, subsidence prediction has attracted interest in geotechnical engineering over the past few decades. Previous research has indicated that the thickness and inclination of seam, depth of working panel, and ground characteristics are the main factors which should be considered in estimating the subsidence. Methods for predicting the subsidence are: empirical, analytical and/or numerical. The geotechnical characteristics of ground affect the caving, collapse, and bulking of goaf and the extent of the cavity toward the surface. The main aim of this paper is to investigate the mechanism of ground surface subsidence based on analytical and numerical simulations. Analytical solutions are based on the theory of elasticity. The Distinct Element Method, which can simulate jointed and stratified rock mass, is used for numerical modelling of subsidence due to mining. In this paper, numerical and analytical results are obtained for two different cases of isotropic and transverse isotropic (layered) strata. Outcomes of this study indicate that the weak planes and stratification not only play a significant role in geotechnical behavior of the rock mass, but they affect the mechanism of ground movement. Results also show that considering the real structure and properties of ground will lead to more accurate estimation of measured subsidence in the field.