In the control of contaminated soil, cut-off walls are often used beneath existing structures or in areas where contaminated soils are widespread, created by mixing soil in situ with cement. These cut-off walls are designed to limit the spread of contaminants into the groundwater and therefore require low permeability. Recently, the permeability of cement-treated soil subjected to the flow of a magnesium solution was investigated. As a result, it was shown that the permeability decreased significantly with increasing flow rate of the magnesium solution, suggesting that magnesium salts contribute to the reduction of permeability in cement-treated soil. In this study, cement-treated soil with added magnesium sulfate was investigated to develop a low-permeability material. As a result, it was confirmed that the permeability of the cement-treated soil decreased as the magnesium sulfate content increased. Instrumental analysis showed that the amount of ettringite formation increased with higher magnesium sulfate content. The reduction in the permeability of the specimens with magnesium sulfate was attributed to the filling of the pores and the increased complexity of the pore structure caused by the formation of ettringite.
This paper presents a comprehensive statistical analysis to evaluate the uncertainties inherited in the lower–upper matrix (LU) decomposition-based random field theory, which is commonly used in geotechnical engineering to model the random spatial variability of soil properties. To facilitate this study, several realisations of Monte Carlo simulation coupled with LU decomposition-based random field theory are made for varying values of input statistical parameters. Thereafter, the statistical parameters are estimated for each simulated random field using the method of maximum likelihood. The results obtained in this study indicate that the LU decomposition-based random field theory does not yield the random field as it is anticipated to be for given input parameters. Ideally, the statistical parameters estimated from the simulated random fields should be nearly equal to the values of input parameters; however, there is significant randomness in the statistical parameters of the simulated random fields. Furthermore, this paper also presents the analysis to evaluate the factors affecting the uncertainties in the random fields simulated by LU decomposition-based theory by varying the input statistical and geometrical parameters.
This study determined the magnitude of the hydraulic anisotropy ratio (rk = kh/kv) in undisturbed tailings samples with varying fines contents. Constant-head permeability tests were performed under different consolidation stress levels and hydraulic gradients, evaluating the influence of effective stress, void ratio, and fines content on the compression index (Cc), the coefficient of consolidation (Cv), and permeability (k). To obtain rk, the experimental method of cutting samples in different directions was implemented. This method has been applied to obtain rk in various materials such as clays and rocks, but it is not known to have been used for tailings. The literature reports few rk values for tailings. According to different researchers, rk in tailings can vary from 2 for fairly uniform dams to 100 in transition zones, due to the intercalation of fine and coarse particles. In this study, rk values ranging from 1 to 10 were obtained, identifying fines content as the main factor controlling hydraulic anisotropy. Furthermore, three correlations were defined between fines content and initial and final void ratios.
This study aimed at investigating the seismic performance of hollow fibre-reinforced polymer (FRP) piles compared to traditional piles in soft clay deposits using shaking table tests. A laminar shear box with dimensions of 1.0 x 1.0 x 1.0 m was used to contain the soil medium and allow it to respond similarly to the free field. Two types of composite group piles (2 x 2) made of carbon fibre-reinforced polymer and glass fibre-reinforced polymer, along with aluminium piles, were manufactured and embedded as end-bearing piles within the soil. Several monitoring instruments were used to observe the soil-pile response under variety of ground motions adopted from the 2010 Val-des-Bois Earthquake in Canada and the 1995 Kobe Earthquake. Seismic response of the foundation was strongly dependent on the stiffness provided by the soil, which was a function of the degree of softening and intensity of shaking. The foundation motion of model piles was higher than those of the free field mainly because of strong kinematic soil-pile interaction. Among the model piles, FRP piles revealed lower foundation motion due to their lower flexural stiffness compared to aluminium piles. This could make FRP piles a remarkably viable option compared to conventional piles under seismic loading.
This study presents a controlled reconstitution method to develop artificially structured soils focusing on lightly cemented kaolin, aiming to replicate natural clay features for laboratory research. It systematically investigates the influence of light cementation, initial water content, curing time, and specimen orientation. Findings show that even 1% cement content significantly increases the yield stress, confirming soil structuration. Initial water content is a decisive factor, as higher values lead to a more open fabric, characterised by larger initial void ratios and pore sizes. Macrostructure tests reveal a brittle failure mode; strength and stiffness increase with cement and curing time, but decrease with higher initial water content. Anisotropy has only a minor influence on compressibility and mechanical properties, attributed to the low reconstitution pressure and early cement hydration 'locking in' a random particle fabric. Microstructural analyses, including SEM, mercury intrusion porosimetry (MIP) and X-ray diffraction (XRD), support these macroscopic observations. SEM images confirm ettringite formation and the progressive filling of inter-aggregate pores with increasing cement. MIP results indicate pore refinement, while XRD analysis indicates a reduction in kaolinite crystallinity due to chemical alteration. This research provides a methodological basis for standardising the preparation of artificially structured soils and advancing the understanding of lightly cemented clay behaviour.
The soil subsidence in goaf will cause the elastic and plastic deformation of pipeline, which will shorten its service life. So it is crucial to study the mechanism of pipe–soil interaction during subsidence and establish the efficient model that can represent the state of soil subsidence, that is, the pipeline health state detection model. This paper studied the spatio-temporal evolution law of soil subsidence process in goaf based on the probability integral method. The stress and strain model of pipe–soil interaction was proposed to describe pipe–soil interaction mechanism. The accuracy of the finite element analysis results is verified by experiments, and the strain error is within 6%, which guarantees the accuracy of the pipe stress–strain-based health monitoring model. Based on the discrete mechanics data obtained from finite element analysis, a hybrid kernel function support vector machine method was proposed to study the continuous mapping model of soil subsidence state–pipeline strain state–stress state, which can calculate the healthy status efficiency and precisely. It lays the foundation for the establishment of the pipeline health condition detection system.
Studying the interaction between voids and retaining structures is vitally important, since the performance of such structures may negatively affected by nearby voids such as aqueducts, metro tunnels, and water collection tunnels in heavily urbanised areas. In this study, the impact of horizontal voids on a soil-nailed wall performance has been investigated. Horizontal deformations and ground surface settlements of a soil-nailed wall, which is close to a void, are analysed by simulation in ABAQUS. The results show that increasing the diameter of the voids leads to the exacerbation of horizontal deformation and vertical ground settlement. At a constant distance from the soil-nailed wall, the void closer to the surface of the ground had a greater destructive influence on wall performance. The worst state for the wall was occurred by a void, having 12 m diameter and situated at 16 m in depth from the surface. The acquired results were 34% and 350% increase for horizontal deformation and ground settlement, respectively.
Seismic events can severely impact earth-retaining structures near deep excavations, disrupting operations, especially in densely populated areas during emergencies and rescue efforts. Rapid assessment of seismic vulnerability is essential for these structures. Fragility curves are effective tools for evaluating earthquake-induced damage. This study focuses on developing fragility functions for embedded cantilever retaining walls. A key innovation of this research is identifying intensity measures (IMs) that strongly correlate with wall responses, addressing gaps in current seismic vulnerability assessments. The study employs an advanced approach by combining static simulations with two-dimensional (2D) dynamic analysis using Plaxis 2D software, allowing an accurate representation of the wall behaviour under earthquake. Thirty-one IMs were evaluated for norms such as efficiency, practicality, proficiency, and sufficiency, resulting in the selection of optimal IMs for the fragility functions. The response of the structure is characterised by a permanent lateral displacement at the top of the wall. Fragility functions were developed for the spectral acceleration, providing a unique tool for assessing the seismic vulnerability of embedded cantilever retaining walls. These proposed tools serve as valuable resources for emergency management and preparedness, aiding in the identification of priority actions and appropriate measures for mitigating seismic risk.
Although the key aim of soil classification systems for engineering purposes is to provide a standardised system for the identification and grouping of soils of similar composition and mechanical properties, there is no common consensus among different soil classification systems. Inconsistencies between different soil classification systems can lead to incorrect foundation and earthworks design and an increase in project time and cost. This paper presents a comparison of two chosen soil classification systems, the Unified Soil Classification System (USCS; ASTM D2487-17-reapproved 2025) and the Australian Soil Classification System (ASCS; AS1726: 2017), by way of extensive laboratory test results, the cone penetration test, and the critical state soil mechanics framework. A distinct difference in fine-grained soil classification has been identified between USCS and ASCS. It has been found that the threshold fines content (i.e. 35%), as adopted in ASCS to differentiate fine-grained soil from coarse-grained soil, is more appropriate compared with the threshold fines content (i.e. 50%) adopted in USCS. Furthermore, categorising soil plasticity into three groups (i.e. low, medium, and high) is assessed to be more practical in engineering practice. This review also highlights the need for a worldwide unified approach in defining organic soils due to their detrimental effect on soil mechanical behaviour.
Stone columns are an effective ground improvement technique for mitigating liquefaction hazards in seismically active regions. This review critically evaluates the mechanisms, applications, and limitations of stone columns through analysis of experimental studies, numerical simulations, and field case histories. The reinforcement effects of stone columns, including enhanced drainage, soil densification, and stress redistribution, are examined. Key design parameters influencing stone column efficacy, such as area replacement ratio and column spacing, are discussed. While stone columns have demonstrated potential in reducing liquefaction-induced deformations, their performance depends on site-specific conditions and design configurations. Challenges associated with stone column implementation, such as clogging and bulging failure under seismic loading, are assessed. Recent advancements in geosynthetic encasement technology show promise in enhancing column stability and drainage capacity. Future research priorities include the development of comprehensive design guidelines, establishment of performance databases, and validation of numerical models through collaborative efforts between researchers and practitioners. This review provides valuable insights to guide the optimisation of stone column technology for enhancing infrastructure resilience in earthquake-prone regions.
Critical state theory evolved through various contributions relating to both sands and clays, but all were based on remoulded or reconstituted samples. This evolution has produced a perception that the theory applies only to ‘structureless’ soils, with the corollary of no relevance to natural soils which have developed structure and/or bonds through geological processes; residual soils are a particular example. A structured residual soil at the Cadia Northern Tailings Storage Facility displayed brittle undrained behaviour comparable to static liquefaction and contributed to a slump of the dam. The effect of structure is conventionally taken into account by expanding a soil’s yield surface but doing so leads to an increased elastic response whereas residual soils normally show plastic strains near immediately. Here we add ‘structure’ to the theory using two additional soil properties, one a true cohesion attributable to structure and the second characterising the rate of decay of that structure with distortion. This extended theory replicates the measured behaviour of the residual soil considered. The extended theory can be used with existing geotechnical modelling software to simulate progressive failure provided that the software includes user-defined routines (‘scripts’) to allow updating of the critical friction ratio as analysis proceeds.
Foamed bitumen stabilisation (FBS) is widely used to enhance durability, moisture resistance, and road flexibility while reducing cracking. Addressing knowledge gaps in its application with recycled materials can expand their usage in road construction. This study focused on stabilising mixes of 50% recycled concrete aggregate (RCA) and 50% fine recycled glass (RG) using foamed bitumen (FB). Recycled toner aggregate (RTA) and geopolymers derived from ground granulated blast furnace slag (S) and fly ash (FA) were evaluated as potential alternatives to conventional secondary binders, such as Portland cement for FBS of recycled material blends. To assess the performance of RTA, a fixed 3% FB dosage was combined with varying RTA amounts (1%-4%). Geopolymers including FA, S, and (FA + S) at dosages of 10%, 20%, and 30% by mass of RCA and RG blend were tested alongside 3% FB for their stabilising effectiveness. FB-stabilised samples with RTA initially failed the indirect tensile modulus tests, but their performance improved significantly after extended curing. The blend incorporating geopolymers, RCA + RG + 3% FB + 20% (FA + S), met local road authority standards. These results demonstrate the potential of sustainable secondary binders for the stabilisation of RCA and RG mixtures in road construction.
The California bearing ratio (CBR) value is a fundamental property used to characterise the strength of the subgrade in road pavement design. CBR calculation in the laboratory is complex, time-consuming, costly, and requires careful execution. A machine learning approach is used to predict CBR of soil treated with hydrated-lime activated rice husk ash (HARHA). The prediction uses an algorithmic approach on A-7-6 expansive soil treated with HARHA, added from 0.1% to 12% in 0.1% increments. Using this approach, 121 distinct data sets were produced in the laboratory which are used to accomplish the stated goals. The data set includes six input parameters: HARHA, liquid-limit, plastic-limit, optimum moisture content, clayey activity, maximum dry density and one output: CBR value. Various models were used, including artificial neural networks (ANN), support vector machine (SVM), Gaussian process regression (GPR), and random forest (RF). The models' performance was evaluated using statistical measures including coefficient of determination, mean absolute error, root mean square error, relative absolute error, and root relative squared error. The evaluation indicates that the RF model had superior predictive performance followed by ANN, SVM, and GPR model. Moreover, sensitivity analysis shows that maximum dry density is the most influential factor on CBR value.
Climate change presents a serious challenge to underground transport infrastructure. Rising temperatures and extreme weather events (EWEs) are causing an increase in geotechnical and structural difficulties. This review looks at important climate-related impacts, such as: (1) sea level rise, which heightens the risk of flooding, increases hydrostatic pressure, and leads to saltwater intrusion, affecting structural stability; (2) EWEs, including heavy rainfall and extreme temperatures, which weaken soils, cause cracks in tunnel linings, and put stress on drainage systems; (3) fluctuations in groundwater, which result in settlement, deformation, seepage, and corrosion; and (4) changes in soil composition due to droughts, floods, and freeze–thaw cycles, diminishing underground stability. These environmental changes have a greater effect on coastal and densely populated urban areas, where increased risks worsen infrastructure weaknesses. A comprehensive approach is necessary to adapt designs, improve geotechnical resilience, and reduce climate-induced risks. This study emphasises the need to incorporate adaptive strategies into infrastructure planning to guarantee long-term safety, functionality, and sustainability. By considering the interactions between climate change and underground systems, this review highlights the importance of proactive measures to safeguard essential transport networks in an environment that is rapidly changing.
Triaxial apparatus is a commonly adopted testing device for understanding the mechanical behaviours of soils from laboratory tests. The uniform distribution of stress–strain inside the specimen till a large strain close to a steady state is a challenge. Over nearly three decades, research at the University of New South Wales, Canberra, has led to notable improvements in triaxial testing techniques. This article reviews both standard and advanced triaxial testing techniques. These include the ability of the triaxial testing device to measure and record instability behaviour, specimen preparation techniques, enlarged platens with free ends, and its effects, accuracy, and errors involved in the different measurements/calculations. A total of 166 critical state data points of Sydney sand with fines and pond ash prepared under different specimen methods and testing conditions have been included to evaluate the effectiveness and reliability of the abovementioned techniques. Representative monotonic and cyclic test results have been presented to further validate the techniques. The results demonstrate that a unique critical state line can be reliably established, enabling the accurate estimation of state parameters to predict instability behaviour using the critical state soil mechanics framework under both static and cyclic loading conditions.
This paper analyses the impact of construction disturbances on the effectiveness of anchor pile protection measures for metro tunnels through laboratory experiments and numerical simulations. Artificially disturbed soil was prepared by incorporating salt grains and varying amounts of cement into remoulded silty clay from Ningbo. One-dimensional compression and triaxial tests were conducted to study the engineering properties of both undisturbed and disturbed soils. The relationship between cement content and disturbance degree was established based on compressibility, shear strength, and structural yield stress, providing parameters for the hardening soil model with small-strain stiffness. Disturbance zones were classified using the unloading ratio and field disturbance tests conducted at the Gaotangqiao metro station excavation site. Using PLAXIS 3D, the study analysed the effects of pit excavation–induced and anchor pile construction–induced disturbances on tunnel displacement. The results indicate that at 2% cement content, disturbed soil properties were essentially equivalent to those of undisturbed soil. Pit excavation–induced disturbances increased the tunnel’s maximum vertical displacement by 18.3%. The maximum uplift and horizontal displacements of the tunnel increased by 18% and 17%, respectively, due to anchor pile construction–induced disturbances. Despite these construction disturbances, the anchor pile construction effectively controlled tunnel displacement compared with unmitigated excavation.
In 2022, the International Civil Aviation Organization (ICAO) introduced the Aircraft Classification Rating – Pavement Classification Rating (ACR-PCR) system, replacing the globally adopted Aircraft Classification Number – Pavement Classification Number (ACN-PCN) system for airfield pavement rating. This paper examines the performance of airfield rigid pavements using Federal Aviation Administration methodologies, analysing two airports with rigid pavements as case studies in the published literature. The study compares results from the ACR-PCR and ACN-PCN methods across 36 types of aircraft. The ACN and ACR values of various aircraft were calculated using different subgrade categories. For a single rigid pavement layer, varying thickness was considered to determine the PCN and PCR values. The results reveal that the ACN-PCN method produces more moderate outcomes than the ACR-PCR method. In addition, rigid pavement thickness significantly influences PCN values compared with PCR. These findings can assist airport administrators in preparing for the transition from the ACN-PCN system to the ACR-PCR system.
To control and ensure the safety of the Madani Tabriz dam at the period 10 years after the end of construction, dam monitoring is performed utilising data from the instrumentation installed on the dam’s body. In this study, using the Midas finite element software, the results of the settlement, pore water pressure, and total stress of the Madani rockfill dam were calculated 10 years after the end of construction of the dam body and compared with the results of the instrumentation observation. The linear correlation coefficients between the data obtained from the sensors and the numerical analysis results for the items of settlement, pore water pressure, and total stress are 84%, 67%, and 99%, respectively. Sensitivity analyses were carried out for present special impounding programme for the dam, with controlling two simultaneous items: the pore water pressure and effect stress changes in the clay core, with 10 years passed since the completion of construction of the dam body. While controlling the reliability coefficient of the body stability, with a 30 cm/d reservoir impounding, the dam reservoir will be filled in 80 d. Suggest an impounding program for a reservoir behind an earth or rockfill dam, detailing a specific plan that ensures all safety aspects of the dam are controlled.
Machine learning techniques establish the relationship between inputs and outputs in numerical simulations, circumventing the need for complex modelling and post-processing. This reduces the expertise and time required, facilitating wider adoption of numerical simulation methods. In this paper, taking the classic geotechnical engineering problem of slope safety factor calculation as an example, a comprehensive methodology for optimising numerical simulations using machine learning is presented. This includes: (a) the determination and quantification of input and output parameters for numerical simulations; (b) the design of the neural network, including the algorithm selection, the structure design, and the activation functions selection; (c) the design of training standards for neural networks; (d) the design of training and test sets using orthogonal and full factorial design methods; and (e) the model performance evaluation and the characteristics of prediction errors analysis. Furthermore, the probability of achieving the acceptable models on a training set and the extrapolation performance of the surrogate model are discussed in detail, which are beneficial for the design of the training sets and training sessions. The paper aims to standardise building and evaluating geotechnical numerical simulation surrogate models using machine learning, easing their application in engineering practice.
In seawater, cement-treated soil undergoes accelerated deterioration owing to enhanced calcium leaching caused by magnesium salts. The deterioration of cement-treated soil progresses gradually from the surface in contact with seawater, necessitating extended periods for investigating the soil properties after deterioration in laboratory tests. However, an accelerated deterioration method for cement-treated soil has not been developed. This study examines the effects of Mg concentration in the immersion water (0.94–23.45 g/l) and specimen dimensions (2.0–5.0 cm in diameter) on the deterioration rate. The aim is to accelerate the production of deteriorated cement-treated soil and characterise soil properties in a short period. The results indicated that the deterioration rate of the cement-treated soil increased with increasing Mg concentration in the immersion water, and the Mg concentration of 23.45 g/l was more than five times faster than that of 0.94 g/l. Furthermore, the smaller the specimen size, the shorter the period required for deterioration. The strength of the deteriorated cement-treated soil varied depending on the size of the specimen; however, the difference was within 16% based on a diameter of 5.0 cm.
