Acid rain of soils has a significant impact on mechanical properties. An X-ray diffraction test, scanning electron microscope (SEM) test, laser particle size analysis test, and triaxial unconsolidated undrained (UU) test were carried out in red clay soils with different compaction degrees under the effect of different concentrations of acid. The experiments demonstrated that: the dissolution effect of acid rain on colluvium weakened with the increase in the compacting degree under the condition of certain pH values, i.e., the damage to the structure of red clay soil was relatively light, where the number of newly increased pores in the soil decreased and the agglomeration of soil particles increased; for the same compacting degree, the structural gap decreased, and the agglomeration increased with the increase in the pH value (acidity decreases) of the acid rain; the dissolution rate of Si, Al, Fe, and other elemental minerals and cement in red clay soil was found to be higher under the effect of acid rain, in turn destroying the original structure of the soil body and producing a large number of pores. This is macroscopically expressed as the decrease of the soil cohesion and internal friction angle, thereby reducing the shear strength of the soil body.

Drained cyclic triaxial tests were conducted on a saturated sand to examine its deformation characteristics under either axial or lateral cyclic loading condition. To apply lateral cyclic loading, the cell pressure was cycled while maintaining a constant vertical stress. The strain accumulations and flow direction in the soil were presented and discussed considering various initial stress ratios (η₀), cyclic stress amplitudes and cyclic stress paths. The results indicate that axial strain accumulation shows an exponential increase with the maximum stress ratio (η^max). The initial deviatoric stress has comparable effects with lateral cyclic stress amplitude on the accumulated axial strain. In contrast, the accumulated volumetric strain is directly proportional to the lateral cyclic stress amplitude but not much affected by η₀ values. Due to the anisotropy of the soil, the accumulated axial and lateral bulging strains are greater in lateral cyclic loading when compared to axial cyclic loading even though η^max is the same. It is also found that η^max affects soil's lateral deformation and increasing the ratio could change the lateral deformation from contraction to bulging. The flow direction depends on η^max in the sand under lateral cyclic loading, regardless of η₀ values and the cyclic stress amplitudes, and a large η^max could lead to great deviatoric strain but a little volumetric strain accumulation.

The practical usage of underground space and demand for vehicular tunnels necessitate the construction of non-circular wide rectangular tunnels. However, constructing large tunnels in soft clayey soil conditions with no ground improvement can lead to excessive ground deformations and collapse. In recent years, in situ ground improvement techniques such as jet grouting and deep cement mixing are often utilized to perform cement-stabilisation around the tunnel boundary to prevent large deformations and failure. This paper discusses the stability characteristics and failure behaviour of a wide rectangular tunnel in cement-treated soft clays. First, the plane strain finite element model is developed and validated with the results of centrifuge model tests available in the past literature. The critical tunnel support pressures computed from the numerical study are found to be in good agreement with those of centrifuge model tests. The influence of varying strength and thickness of improved soil surround, and cover depth are studied on the stability and failure modes of a rectangular tunnel. It is observed that the failure behaviour of the tunnel in improved soil surround depends on the ratio of the strength of improved soil surround to the strength of surrounding soil, i.e., q_ui/q_us, rather than just q_ui. For low q_ui/q_us ratios,the stability increases with the cover; however, for the high strength improved soil surrounds with q_ui >> q_us, the stability decreases with the cover. The failure chart, modified stability equation, and stability chart are also proposed as preliminary design guidelines for constructing rectangular tunnels in the improved soil surrounded by soft clays.

Accurately estimation of the geo-mechanical parameters in Artificial Ground Freezing (AGF) is a most important scientific topic in soil improvement and geotechnical engineering. In order for this, one way is using classical and conventional constitutive models based on different theories like critical state theory, Hooke's law, and so on, which are time-consuming, costly, and troublous. The others are the application of artificial intelligence (AI) techniques to predict considered parameters and behaviors accurately. This study presents a comprehensive data-mining-based model for predicting the Young's Modulus of frozen sand under the triaxial test. For this aim, several single and hybrid models were considered including additive regression, bagging, M5-Rules, M5P, random forests (RF), support vector regression (SVR), locally weighted linear (LWL), gaussian process regression (GPR), and multi-layered perceptron neural network (MLP). In the present study, cell pressure, strain rate, temperature, time, and strain were considered as the input variables, where the Young's Modulus was recognized as target. The results showed that all selected single and hybrid predicting models have acceptable agreement with measured experimental results. Especially, hybrid Additive Regression-Gaussian Process Regression and Bagging-Gaussian Process Regression have the best accuracy based on Model performance assessment criteria.

The coupled soil-pile-structure seismic response is recently in the spotlight of researchers because of its extensive applications in the different fields of engineering such as bridges, offshore platforms, wind turbines, and buildings. In this paper, a simple analytical model is developed to evaluate the dynamic performance of seismically isolated bridges considering triple interactions of soil, piles, and bridges simultaneously. Novel expressions are proposed to present the dynamic behavior of pile groups in inhomogeneous soils with various shear modulus along with depth. Both cohesive and cohesionless soil deposits can be simulated by this analytical model with a generalized function of varied shear modulus along the soil depth belonging to an inhomogeneous stratum. The methodology is discussed in detail and validated by rigorous dynamic solution of 3D continuum modeling, and time history analysis of centrifuge tests. The proposed analytical model accuracy is guaranteed by the acceptable agreement between the experimental/numerical and analytical results. A comparison of the proposed linear model results with nonlinear centrifuge tests showed that during moderate (frequent) earthquakes the relative differences in responses of the superstructure and the pile cap can be ignored. However, during strong excitations, the response calculated in the linear time history analysis is always lower than the real conditions with the nonlinear behavior of the soil-pile-bridge system. The current simple and efficient method provides the accuracy and the least computational costs in comparison to the full three-dimensional analyses.

We evaluated the applicability of machine learning techniques and the Kuz-Ram model for predicting the mean fragmentation size in open-pit mines. The characteristics of the in-situ rock considered here were uniaxial compressive strength, tensile strength, rock factor, and mean in-situ block size. Seventy field datasets that included these characteristics were collected to predict the mean fragmentation size. Deep neural network, support vector machine, and extreme gradient boosting (XGBoost) models were trained using the data. The performance was evaluated using the root mean squared error (RMSE) and the coefficient of determination (r²). The XGBoost model had the smallest RMSE and the highest r² value compared with the other models. Additionally, when analyzing the error rate between the measured and predicted values, XGBoost had the lowest error rate. When the Kuz-Ram model was applied, low accuracy was observed owing to the differences in the characteristics of data used for model development. Consequently, the proposed XGBoost model predicted the mean fragmentation size more accurately than other models. If its performance is improved by securing sufficient data in the future, it will be useful for improving the blasting efficiency at the target site.

This study investigates to provide a fast solution to the problem of bearing capacity in layered soils with easily obtainable parameters that does not require the use of any charts or calculations of different parameters. Therefore, a hybrid approach including both the finite element (FE) method and machine learning technique have been applied. Firstly, a FE model has been generated which is validated by the results of in-situ loading tests. Then, a total of 192 three-dimensional FE analyses have been performed. A data set has been created utilizing the soil properties, footing sizes, layered conditions used in the FE analyses and the ultimate bearing capacity values obtained from the FE analyses to be used in multigene genetic programming (MGGP). Problem has been modeled with five input and one output parameter to propose a bearing capacity formula. Ultimate bearing capacity values estimated from the proposed formula using data set consisting of 20 data independent of total data set used in MGGP modelling have been compared to the bearing capacities calculated with semi-empirical methods. It was observed that the MGGP method yielded successful results for the problem considered. The proposed formula provides reasonable predictions and efficient enough to be used in practice.

A dynamic triaxial discrete element numerical model of lightweight soil was established using the discrete element method to study the microscopic mechanism of expanded polystyrene (EPS) particles in the soil under cyclic loading. The microscopic parameters of the discrete element model of the lightweight soil were calibrated depending on the dynamic triaxial test hysteresis curves. Based on the calibration results, the effects of the EPS particles volume ratio and amplitude on the contact force, displacement field, and velocity field of the lightweight soil under different accumulated strains were studied. The results showed that the hysteresis curves of lightweight soil exhibit nonlinearity, hysteresis, and strain accumulation. The strain accumulated in remolded soil is mainly tensile strain, and that in lightweight soil is mainly compressive strain. As the volume ratio of EPS particles increased, the contact force first increased and then decreased, and the displacement and velocity of the particles increased accordingly. With an increase in amplitude, the dynamic stress of the particle system increased, and the accumulation rate of the dynamic strain of the samples also increased. At 5% compressive strain, the contact force of the particles changed significantly and the number of particles deflected in the direction of velocity also increased considerably. These results indicated that the cemented structure of the lightweight soil began to fail at a compressive strain of 5%. Thus, a compressive strain of 5% is more reasonable than the dynamic strength failure standard of lightweight soil.