Seismic ground response evaluation is one of the main issues in geotechnical earthquake engineering. These analyses are subsequently divided into one-, two- and three-dimensional methods, and each of which can perform in time or frequency domain. In this study, a novel approach is proposed to assess the seismic site response using two-dimensional transfer functions in frequency domain analysis. Using the proposed formulation, a program is written in MATLAB environment and then promoted utilizing the equivalent linear approach. The accuracy of the written program is evaluated by comparing the obtained results with those of actual recorded data in the Gilroy region during Loma Prieta (1989) and Coyote Lake (1979) earthquakes. In order to precise comparison, acceleration time histories, Fourier amplitude spectra and acceleration response spectra diagrams of calculated and recorded data are presented. The proposed 2D transfer function diagrams are also obtained using mentioned earthquakes which show the amount of amplification or attenuation of the input motion at different frequencies while passing through the soil layer. The results of the proposed method confirm its accuracy and efficiency to evaluate ground motion during earthquakes using two-dimensional model. Then, studies on irregular topographies are carried out, and diagrams of amplification factors are shown.

One of the most important issues in tunneling, is the squeezing phenomenon. Squeezing can occur during excavation or after the construction of tunnels, which in both cases could lead to significant damages. Therefore, it is important to predict the squeezing and consider it in the early design stage of tunnel construction. Different empirical, semi-empirical and theoretical-analytical methods have been presented to determine the squeezing. Therefore, it is necessary to examine the ability of each of these methods and identify the best method among them. In this study, squeezing in a part of the Alborz service tunnel in Iran was estimated through a number of empirical, semi- empirical and theoretical-analytical methods. Among these methods, the most robust model was used to obtain a database including 300 data for training and 33 data for testing in order to develop a machine learning (ML) method. To this end, three ML models of Gaussian process regression (GPR), artificial neural network (ANN) and support vector regression (SVR) were trained and tested to propose a robust model to predict the squeezing phenomenon. A comparative analysis between the conventional and the ML methods utilized in this study showed that, the GPR model is the most robust model in the prediction of squeezing phenomenon. The sensitivity analysis of the input parameters using the mutual information test (MIT) method showed that, the most sensitive parameter on the squeezing phenomenon is the tangential strain (ε_θ^α) parameter with a sensitivity score of 2.18. Finally, the GPR model was recommended to predict the squeezing phenomenon in tunneling projects. This work's significance is that it can provide a good estimation of the squeezing phenomenon in tunneling projects, based on which geotechnical engineers can take the necessary actions to deal with it in the pre-construction designs.

Gravelly soil is a kind of special geotechnical material, which is widely used in the subgrade engineering of railway, highway and airport. Its mechanical properties are very complex, and will greatly influence the stability of subgrade engineering. To investigate the mechanical properties and failure mechanism of gravelly soils, this paper introduced and verified a new discrete element method (DEM) of gravelly soils in large scale direct shear test, which considers the actual shape and broken characteristics of gravels. Then, the stress and strain characteristics, particle interaction, particle contact force, crack development and energy conversion in gravelly soils during the shear process were analyzed using this method. Moreover, the effects of gravel content (GC) on the mechanical properties and failure characteristics were discussed. The results reveal that as GC increases, the shear stress becomes more fluctuating, the peak shear stress increases, the volumetric strain tends to dilate, the average particle contact force increases, the cumulative number of cracks increases, and the shear failure plane becomes coarser. Higher GC will change the friction angle with a trend of "stability", "increase", and "stability". Differently, it affects the cohesion with a law of "increase", "stability" and "increase".

In the present study, a physical model was built for the Jintan underground gas storage cavern group according to the similarity theory. In this regard, four ellipsoid caverns were built with scaled in-situ stresses and internal pressure. Then the stability of underground caverns was analyzed. The obtained results demonstrate that loss of internal pressure adversely affects the safety of caverns and attention should be paid during the operation of gas storage.

The article presents the results of finite element analyses carried out on skirted footings. The bearing capacity increases with the provision of the flexible and rigid skirt, but the effectiveness varies with various other factors. The skirts are more efficient in the case of cohesionless soils than cohesive and c-ϕ soils. Efficiency reduces with an increase in the soil strength and footing depth. The rigid skirt is relatively more efficient compared to the flexible skirt. In contrast, to the flexible skirt, the efficiency of the rigid skirt increases continuously with skirt length. The difference in the effectiveness of both skirts becomes more noticeable with an increase in the strength parameters, skirt length, and footing depth. The failure mechanism also changes significantly with the inclusion of a rigid skirt. The rigid skirt behaves as a solid embedded footing, and the failure mechanism becomes confined with an increase in the skirt length. Few small-scale laboratory tests were carried out to study the flexible and rigid skirt and verify the numerical study results. The numerical analysis results are further used to develop nonlinear equations to predict the enhancement in bearing capacity with the provision of the rigid and flexible skirts.

In this study, the fiber orientation distribution (FOD) is investigated using both micro-CT (computerized tomography) and image analysis of physically cut specimens prepared from Polyvinyl Alcohol (PVA) fiber reinforced cemented Toyoura sand. The micro-CT images of the fiber reinforced cemented sand specimens were visualized in horizontal and vertical sections. Scans were obtained using a frame rate of two frames and an exposure time of 500 milliseconds. The number of images was set to optimize and typically resulted in approximately 3000 images. Then, the angles of the fibers for horizontal sections and in vertical section were calculated using the VGStudio MAX software. The number of fibers intersecting horizontal and vertical sections are counted using these images. A similar approach was used for physically cut specimens. The variation of results of fiber orientation between micro-CT scans and visual count were approximately 4-8%. The micro-CT scans were able to precisely investigate the fiber orientation distribution of fibers in these samples. The results show that 85-90% of the PVA fibers are oriented between ±30° of horizontal, and approximately 95% of fibers have an orientation that lies within ±45° of the horizontal plane. Finally, a comparison of experimental results with the generalized fiber orientation distribution function 𝜌(θ) is presented for isotropic and anisotropic distribution in fiber reinforced cemented Toyoura sand specimens. Experimentally, it can be seen that the average ratio of the number of fibers intersecting the finite area on a vertical plane to number of fibers intersecting the finite area on a horizontal plane (N^V_tot/N^H_tot) cut through a sample varies from 2.08 to 2.12 (an average ratio of 2.10 is obtained in this study). Based up on the analytical predictions, it can be seen that the average N^V_tot/N^H_tot ratio varies from 2.13 to 2.17 for varying n values (an average ratio of 2.15).

This paper aims to show how to use several Machine Learning (ML) methods to estimate the TBM penetration rate systematically (TBM-PR). To this end, 1125 datasets including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), punch slope index (PSI), distance between the planes of weakness (DPW), orientation of discontinuities (alpha angle-α), rock fracture class (RFC), and actual/measured TBM-PRs were established. To evaluate the ML methods' ability to perform, the 5-fold cross-validation was taken into consideration. Eventually, comparing the ML outcomes and the TBM monitoring data indicated that the ML methods have a very good potential ability in the prediction of TBM-PR. However, the long short-term memory model with a correlation coefficient of 0.9932 and a route mean square error of 2.68E-6 outperformed the remaining six ML algorithms. The backward selection method showed that PSI and RFC were more and less significant parameters on the TBM-PR compared to the others.

With the exploitation of natural resources in China, underground resource extraction and underground space development, as well as other engineering activities are increasing, resulting in the creation of many defective rocks. In this paper, uniaxial compression tests were performed on rocks with double holes and fractures at different angles using particle flow code (PFC2D) numerical simulations and laboratory experiments. The failure behavior and mechanical properties of rock samples with holes and fractures at different angles were analyzed. The failure modes of rock with defects at different angles were identified. The fracture propagation and stress evolution characteristics of rock with fractures at different angles were determined. The results reveal that compared to intact rocks, the peak stress, elastic modulus, peak strain, initiation stress, and damage stress of fractured rocks with different fracture angles around holes are lower. As the fracture angle increases, the gap in mechanical properties between the defective rock and the intact rock gradually decreased. In the force chain diagram, the compressive stress concentration range of the combined defect of cracks and holes starts to decrease, and the model is gradually destroyed as the tensile stress range gradually increases. When the peak stress is reached, the acoustic emission energy is highest and the rock undergoes brittle damage. Through a comparative study using laboratory tests, the results of laboratory real rocks and numerical simulation experiments were verified and the macroscopic failure characteristics of the real and simulated rocks were determined to be similar. This study can help us correctly understand the mechanical properties of rocks with defects and provide theoretical guidance for practical rock engineering.