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The design of cantilever pile walls (CPWs) presents several common challenges. These challenges include soil variability, groundwater conditions, complex loading conditions, construction considerations, structural integrity, uncertainties in design parameters and construction and monitoring costs. Accordingly, this paper is to provide a detailed literature review on the design criteria of CPWs, specifically in cohesionless soil. This study aims to present a comprehensive overview of the current state of knowledge in this area.

The paper uses a literature review approach to gather information on the design criteria of CPWs in cohesionless soil. It covers various aspects such as excavation support systems (ESSs), deformation behavior, design criteria, lateral earth pressure calculation theories, load distribution methods and conventional design approaches.

The review identifies and discusses common challenges associated with the design of CPWs in cohesionless soil. It highlights the uncertainties in determining load distribution and the potential for excessive wall deformations. The paper presents various approaches and methodologies proposed by researchers to address these challenges.

The paper contributes to the field of geotechnical engineering by providing a valuable resource for geotechnical engineers and researchers involved in the design and analysis of CPWs in cohesionless soil. It offers insights into the design criteria, challenges and potential solutions specific to CPWs in cohesionless soil, filling a gap in the existing knowledge base. The paper draws attention to the limitations of existing analytical methods that neglect the serviceability limit state and assume rigid plastic soil behavior, highlighting the need for improved design approaches in this context.

The soft stabilized slab and pile-supported (SSPS) embankment is an improvement technique to increase the efficiency of resources in road construction. To capture the effects of stabilized slabs on the stress transfer mechanism, the differential settlements and the lateral displacement of the embankment completely. A theoretical model of SSPS is proposed by considering the effect of soil arching and the interaction between the embankment fill, stabilized soil, pile, foundation soil and bearing stratum.

In the theoretical model, the stress and strain coordination relationship of the system was analyzed in view of the minimum potential energy theory and equal settlement plane theory. Subsequently, the theoretical method was applied to field tests for comparison. Finally, the influence of the elastic modulus and the thickness of the stabilized slab on the stress concentration ratio and foundation settlement were examined.

In addition to the experimental findings, the method has been revealed to be reasonable and feasible, considering its ability to effectively exploit the stabilized slab effect and improve the bearing capacity of soil and piles. An economical and reasonable arrangement scheme for the thickness and strength of stabilized slabs was obtained. The results reveal that the optimum elastic modulus was chosen as 28 MPa–60 MPa, and the optimum thickness of the stabilized slab was selected as 1.5 m–2.1 m using the parameters of field tests, which can provide guidance to engineering design.

An optimization calculation method is established to analyze the load transfer mechanics of the SSPS embankment based on a double-equal settlement plane. The model’s rationality was analyzed by comparing the settlement and stress concentration ratios in the field tests. Subsequently, the influence of the elastic modulus and the thickness of the stabilized slab on the stress concentration ratio and settlement were examined. An economical and reasonable arrangement scheme for the thickness and elastic modulus of stabilized slabs was obtained, which can provide a novel approach for engineering design.

The experiments of this study investigated the effect of the subgrade degree of saturation on the value of the stresses generated on the surface and the middle (vertical and lateral stresses). The objectives of this study can be identified by studying the effect of subgrade layer degree of saturation variation, load amplitude and load frequency on the transmitted stresses through the ballast layer to the subgrade layer and the stress distribution inside it and investigating the excess pore water pressure development in the clay layer in the case of a fully saturated subgrade layer and the change in matric suction in the case of an unsaturated subgrade layer.

Thirty-six laboratory experiments were conducted using approximately half-scale replicas of real railways, with an iron box measuring 1.5 x 1.0 × 1.0 m. Inside the box, a 0.5 m thick layer of clay soil representing the base layer was built. Above it is a 0.2 m thick ballast layer made of crushed stone, and on top of that is a 0.8 m long rail line supported by three 0.9 m (0.1 × 0.1 m) slipper beams. The subgrade layer has been built at the following various saturation levels: 100, 80, 70 and 60%. Experiments were conducted with various frequencies of 1, 2 and 4 Hz with load amplitudes of 15, 25 and 35 kN.

The results of the study demonstrated that as the subgrade degree of saturation decreased from 100 to 60%, the ratio of stress in the lateral direction to stress in the vertical direction generated in the middle of the subgrade layer decreased as well. On average, this ratio changed from approximately 0.75 to approximately 0.65.

The study discovered that as the test proceeded and the number of cycles increased, the value of negative water pressure (matric suction) in the case of unsaturated subgrade soils declined. The frequency of loads had no bearing on the ratio of decline in matric suction values, which was greater under a larger load amplitude than a lower one. As the test progressed (as the number of cycles increased), the matric suction dropped. For larger load amplitudes, there is a greater shift in matric suction. The change in matric suction is greater at higher saturation levels than it is at lower saturation levels. Furthermore, it is seen that the load frequency value has no bearing on how the matric suction changes. For all load frequencies and subgrade layer saturation levels, the track panel settlement rises with the load amplitude. Higher load frequency and saturation levels have a greater impact.

Designing a sustainable bituminous concrete with long-term performance is a challenging problem. In addition, strength of the subgrade has a crucial impact on pavement design. This paper aims to concentrate on subgrade soil stabilization with granite dust powder (GDP) and crumb rubber powder (CRP) to improve the engineering properties of the soil. Further design of bituminous concrete pavement with cement-treated layers in base and subbase course layers was carried out with life cycle cost analysis and life cycle assessment for 1 km of a four-lane national highway.

Subgrade soil stabilized with GDP and CRP is characterized as per Indian Standards (IS)-2720 to determine the optimum dosage. Further, the mechanistic-empirical pavement design was carried out using Indian Road Congress-37 (2018), analyzed using IITPAVE software and validated with ANSYS software. The life cycle cost analysis is carried out using the net present value method, and the life cycle assessment is performed according to the cradle-to-grave approach.

A soil mix comprising 10% GDP and 2.5% CRP yielded a soaked California bearing ratio value of 6.58%. In addition, the design of bituminous concrete pavement with cement-treated granular layers showed a 26.9% reduction in life cycle cost and 59.4% reduction in total carbon footprint per kilometer compared to the pavement with traditional aggregate layers.

The research on subgrade stabilization with sustainable materials like GDP and CRP incorporating mechanistic empirical pavement design, life cycle cost analysis and life cycle assessment is limited. Overall, the study recommends the use of GDP and CRP to stabilize soil for subgrade application and incorporate cement-treated granular layers, which offer economic and environmental benefits compared to traditional pavement construction.

The paper aims to clarify the distribution of excess pore pressure during cone penetration in two-layered clay and its influence on penetrometer resistance.

An arbitrary Lagrangian–Eulerian scheme is adopted to preserve the quality of mesh throughout the numerical simulation. Simplified methods of layered penetration and coupled pore pressure analysis of cone penetration have been proposed and verified by previous studies. The investigation is then extended by the present work to study the cone penetration test in a two-layered clay profile assumed to be homogeneous with the modified Cam clay model.

The reduction of the range of pore pressure with decreasing PF will cause a decrease of the sensing distance. The PF of the underlying soil is one of the factors that determine the development distance. The interface can be obtained by taking the position of the maximum curvature of the penetrometer resistance curve in the case of stiff clay overlying soft clay. In the case of soft clay overlying stiff clay, the interface locates at the maximum curvature of the penetrometer resistance curve above about 1.6D.

The cone penetration analyses in this paper are conducted assuming smooth soil-cone contact.

A simplified method based on ALE in Abaqus/Explicit is proposed for layered penetration, which solves the problem of mesh distortion at the interface between two materials. The stiffness equivalent method is also proposed to couple pore pressure during cone penetration, which achieves efficient coupling of pore water pressure in large deformations.

This study aims to examine the reuse of plastic and fly ash (FA) to improve the soil and achieve sustainable development goals.

Sand from the Anzali port was reinforced with Geopet (GP) and stabilized with FA plus 3% sodium hydroxide. The GP was placed in FA-stabilized soil and the California bearing ratio (CBR), and unconfined compressive strength (UCS) tests were performed on samples at the optimum moisture content.

The results showed that the improvement in the optimum CBR was 174.9%. The UCS increased 15.25% and 48.65% in soil reinforced with three layers of GP plus 15% FA over those containing 10% and 5% FA, respectively. Additionally, the current analysis used response surface methodology (RSM) to investigate the impact of FA percentage, GP layers and their interaction on CBR. The results highlight the efficacy of the used RSM model, as evidenced by the significantly low p-value (<0.0001).

This demonstrates the suitability and effectiveness of RSM for evaluating CBR in this scientific study.

This study establishes a method for predicting ground vibrations caused by railway tunnels in unsaturated soils with spatial variability.

First, an improved 2.5D finite-element-method-perfect-matching-layer (FEM-PML) model is proposed. The Galerkin method is used to derive the finite element expression in the ub-pl-pg format for unsaturated soil. Unlike the ub-v-w format, which has nine degrees of freedom per node, the ub-pl-pg format has only five degrees of freedom per node; this significantly enhances the calculation efficiency. The stretching function of the PML is adopted to handle the unlimited boundary domain. Additionally, the 2.5D FEM-PML model couples the tunnel, vehicle and track structures. Next, the spatial variability of the soil parameters is simulated by random fields using the Monte Carlo method. By incorporating random fields of soil parameters into the 2.5D FEM-PML model, the effect of soil spatial variability on ground vibrations is demonstrated using a case study.

The spatial variability of the soil parameters primarily affected the vibration acceleration amplitude but had a minor effect on its spatial distribution and attenuation over time. In addition, ground vibration acceleration was more affected by the spatial variability of the soil bulk modulus of compressibility than by that of saturation.

Using the 2.5D FEM-PML model in the ub-pl-pg format of unsaturated soil enhances the computational efficiency. On this basis, with the random fields established by Monte Carlo simulation, the model can calculate the reliability of soil dynamics, which was rarely considered by previous models.

In order to explore a new estimation approach of hyperspectral estimation, this paper aims to establish a hyperspectral estimation model of soil organic matter content with the principal gradient grey information based on the grey information theory.

Firstly, the estimation factors are selected by transforming the spectral data. The eigenvalue matrix of the modelling samples is converted into grey information matrix by using the method of increasing information and taking large, and the principal gradient grey information of modelling samples is calculated by using the method of pro-information interpolation and straight-line interpolation, respectively, and the hyperspectral estimation model of soil organic matter content is established. Then, the positive and inverse grey relational degree are used to identify the principal gradient information quantity of the test samples corresponding to the known patterns, and the cubic polynomial method is used to optimize the principal gradient information quantity for improving estimation accuracy. Finally, the established model is used to estimate the soil organic matter content of Zhangqiu and Jiyang District of Jinan City, Shandong Province.

The results show that the model has the higher estimation accuracy, among the average relative error of 23 test samples is 5.7524%, and the determination coefficient is 0.9002. Compared with the commonly used methods such as multiple linear regression, support vector machine and BP neural network, the hyperspectral estimation accuracy of soil organic matter content is significantly improved. The application example shows that the estimation model proposed in this paper is feasible and effective.

The estimation model in this paper not only fully excavates and utilizes the internal grey information of known samples with “insufficient and incomplete information”, but also effectively overcomes the randomness and grey uncertainty in the spectral estimation. The research results not only enrich the grey system theory and methods, but also provide a new approach for hyperspectral estimation of soil properties such as soil organic matter content, water content and so on.

The paper succeeds in realizing both a new hyperspectral estimation model of soil organic matter content based on the principal gradient grey information and effectively dealing with the randomness and grey uncertainty in spectral estimation.

Explore the development trend of chemically-improved soil in railway engineering.

In this paper, the technical standards home and abroad were analyzed. Laboratory test, field test and monitoring were carried out.

The performance design system of the chemically-improved soil should be established.

On the basis of the performance design, the test methods and standards for various properties of chemically-improved soil should be established to evaluate the improvement effect and control the engineering quality.

The purpose of this paper is to develop an appropriate machine learning model for predicting soil compaction degree while also examining the contribution rates of three influential factors: moisture content, electrical conductivity and temperature, towards the prediction of soil compaction degree.

Taking fine-grained soil A and B as the research object, this paper utilized the laboratory test data, including compaction parameter (moisture content), electrical parameter (electrical conductivity) and temperature, to predict soil degree of compaction based on five types of commonly used machine learning models (19 models in total). According to the prediction results, these models were preliminarily compared and further evaluated.

The Gaussian process regression model has a good effect on the prediction of degree of compaction of the two kinds of soils: the error rates of the prediction of degree of compaction for fine-grained soil A and B are within 6 and 8%, respectively. As per the order, the contribution rates manifest as: moisture content > electrical conductivity >> temperature.

By using moisture content, electrical conductivity, temperature to predict the compaction degree directly, the predicted value of the compaction degree can be obtained with higher accuracy and the detection efficiency of the compaction degree can be improved.