Geotechnics, Volume 5, Issue 1 (March 2025) – 9 articles

Enhancing the engineering properties of clayey soils is crucial for improving their performance in construction projects. Determining the optimal lime dosage using the Chemical Fixation Point (CFP) concept presents challenges due to soil variability, interactions with chemical and organic components, and limitations in environmental or equipment conditions, especially in pH-based methods. These challenges are exacerbated when non-standard lime or lime residues replace conventional lime. This study highlights the plasticity limit as a key parameter for optimizing lime dosage and assessing treatment effectiveness with lime residues. By analyzing four lean clay soils through CFP tests, plasticity limit measurements, and resistance evaluations, an improved methodology for CFP determination using pH–dosage curves is proposed. The findings validate the feasibility of lime residues, emphasize the plasticity limit’s critical role in lean clay treatment, and extend its relevance to soil stabilization. This work enhances CFP test accuracy and supports sustainable, adaptable soil improvement strategies. Full article

This study investigates the impact of sand-induced ballast fouling on railway track performance, focusing on track stiffness (modulus), settlement, and overall degradation. The research utilized an 18-cubic-foot ballast box designed to replicate real-world track conditions under controlled laboratory settings. A key focus was quantifying voids within clean ballast to establish baseline characteristics, which provided a foundation for evaluating the effects of sand fouling. Two distinct test series were conducted to comprehensively analyze track behavior. The first series investigated pre-existing fouling by thoroughly mixing sand into the ballast to achieve uniform fouling levels. The second series simulated natural fouling processes by progressively adding sand from the top of the ballast layer, mimicking real-world conditions such as those in sandy environments. These methodologies allowed for detailed analysis of changes in track stiffness, deflection, and settlement under varying fouling levels. The findings demonstrate a direct correlation between increasing sand fouling levels and heightened track stiffness and settlement. Dynamic load testing revealed that as void spaces were filled with sand, the track’s flexibility and drainage capacity was significantly compromised, leading to accelerated degradation of track geometry. Settlement patterns and deflection data provided critical insights into how fouling adversely affects track performance. These results contribute significantly to understanding the broader implications of sand-induced fouling on track degradation, offering valuable insights for railway maintenance and design improvements. By integrating void analysis, test series data, and load-deflection relationships, this study provides actionable recommendations for enhancing railway infrastructure resilience and optimizing maintenance strategies in sandy terrains. Full article

Designing petroleum tanks that are inter-related with pipelines in a founding position containing very compressible soil are a challenging task, particularly when a possible high-water table and considerably high seismicity are also present. Some of the issues that occur are the problems of the time dependence of settlement behavior as well as the earthquake response of the soil–structure interaction system. This work intends to portray the following: (a) an estimation of the foundations and the corresponding consolidation time response and (b) the earthquake-induced geohazard as well as the soil–structure interaction considered for the foundation of the tanks alongside pipelines in a suburban area in Greece, namely Kalochori of Thessaloniki. A numerical analysis considering the dynamic and static behavior and inter-relation among the soil mass and the buried pipeline alongside the system of the foundation type and the soil beneath is performed. Also, the foundation type that was finally chosen as the optimized solution, namely the set of gravel piles and the subsequent prestress loading, is presented and discussed. Taking into account that the soil in the vicinity of the foundation will have its shear strength during an earthquake decreased to almost zero, risk reduction actions may be suggested for large stresses imposed on the pipeline. The methodology for the dimensionality of the gravel pile group as well as the preloading session indicate that a substantial reduction in the displacements of more than 50% is obtained with the combination of the methods, something that would not be feasible if the methods were implemented individually. Full article

In deep foundation pit engineering, the soil undergoes a complex stress path, encompassing both loading and unloading phases. The Shanghai model, an advanced constitutive model, effectively accounts for the soil’s deformation characteristics under these varied stress paths, which is essential for accurately predicting the horizontal displacement and surface settlement of the foundation pit’s enclosure structure. This model comprises eight material parameters, three initial state parameters, and one small-strain parameter. Despite its sophistication, there is a scarcity of numerical studies exploring the correlation between these parameters and the deformation patterns in foundation pit engineering. This paper initially establishes the superiority of the Shanghai model in ultra-deep circular vertical shaft foundation pit engineering by examining a case study of a nursery circular ultra-deep vertical shaft foundation pit, which is part of the Suzhou River section’s deep drainage and storage pipeline system pilot project in Shanghai. Subsequently, utilizing an idealized foundation pit engineering model, a comprehensive sensitivity analysis of the Shanghai model’s multi-parameter values across their full range was performed using orthogonal experiments. The findings revealed that the parameter most sensitive to the lateral displacement of the underground continuous wall was κ, with an increase in κ leading to a corresponding increase in displacement. Similarly, the parameter most sensitive to surface subsidence outside the pit was λ, with an increase in λ resulting in greater subsidence. Lastly, the parameter most sensitive to soil uplift at the bottom of the pit was also κ, with an increase in κ leading to more significant uplift. Full article

Sub-surface soil hydrological characterization is one of the challenging tasks for engineers and soil scientists, especially the complex hydrological processes that combine key variables such as soil moisture, matric suction, and soil temperature. The ability to infer these variables through a singular measurable soil property, soil resistivity, can potentially improve sub-surface characterization. This research leverages various machine learning algorithms to develop predictive models trained on a comprehensive dataset of sensor-based soil moisture, matric suction, and soil temperature obtained from prototype ET covers, with known resistivity values. Different types of sensors were installed at multiple depths in the ET covers, and resistivity tests were conducted periodically at the same location. Cross-validation and feature selection methods were used to optimize model performance and identify key variables that most significantly impact soil resistivity. Strong inverse correlations between soil moisture and resistivity (r = −0.88) and weak positive correlations with temperature (r = 0.41) and suction (r = 0.34) were observed. Among the machine learning models evaluated, artificial neural networks and support vector machines demonstrated superior predictive performance, achieving a coefficient of determination (R²) above 0.77 and lower root mean square error (RMSE) values (less than 0.14). Linear regression and decision tree models exhibited suboptimal performance because of their limitations in capturing non-linear relationships and overfitting, respectively. Random forest demonstrated superior generalization capabilities compared to decision trees; however, it encountered challenges with mid-range data variability. The findings demonstrate the effectiveness of artificial neural networks in predicting field-scale soil resistivity by utilizing hydrological variables. Full article

Middle–Late Miocene clay layers, which occur in several places in Budapest (Hungary), contain varying amounts of sand, with predominance of sand in some cases. In this paper, the impact of this variability on the engineering properties of these clays is investigated, and comprehensive analysis is conducted on clay samples. The results of measurements are presented; in addition to the analysis of plastic soil (i.e., liquid limit, plasticity index), the grain size distribution was also investigated by performing standard geotechnical laboratory tests, including Atterberg limit tests and grain size analyses. Statistical analysis of the results was employed to define correlations between sand contents and both the liquid limit and the plasticity index. It was shown that both the plasticity index and the liquid limit decrease linearly with increasing sand content. This finding aligns with observations reported in the international literature. A general equation was derived to quantify this relationship, setting up a method for better estimation of the plastic properties of similar clay soils based on their sand content and a better understanding of the engineering geological behaviors of clay soils with varying sand content, which as a result have a practical implication for geotechnical engineers. Full article

The composition of oil sands tailings is a complex mixture of water, fine clay, sand, silt, and residual bitumen that remains after the extraction of bitumen. Effective tailings disposal management requires an understanding of the mechanisms controlling water movement, surface settlement rates and extents (hydraulic conductivity and compressibility), and strength variation with depth. This investigation examines the self-weight consolidation behavior of oil sands tailings, typically assessed by utilizing large strain consolidation (LSC) methods such as the multi-step large strain consolidation (MLSC) test and seepage-induced consolidation test (SICT). These methods, however, are time consuming and often take weeks or years to complete. As an alternative, centrifuge testing, including both geotechnical beam type and benchtop devices, was utilized to evaluate the consolidation behaviors of three untreated high water content oil sands tailing slurries: two high-plasticity fluid fine tailing (FFT) samples and one low plasticity FFT. The centrifuge-derived compressibility data closely matched the LSC testing compressibility data within the centrifuge stress range. However, the hydraulic conductivity obtained from centrifuge testing was up to an order of magnitude higher than the LSC test results. Comparing centrifuge and large strain modeling results indicates that centrifuge test data demonstrate average void ratios 10–33% lower than those predicted by simulations using LSC parameters, highlighting a notable deviation. To examine the scale effect on result accuracy, validation tests indicated that the benchtop centrifuge (BTC) yielded comparable results to the geotechnical beam centrifuge (GBC) for the same prototype, saving time, resources, and sample volumes in the assessment of tailings consolidation behavior. These tests concluded that the small radius of the benchtop centrifuge had a minimal impact on the results. Full article

Hydrogeochemical processes contribute to long-term alterations in key physical properties of a porous medium, including porosity, tortuosity, and permeability, making it essential to understand their evolution and address clogging-dominated problems in hydrogeological systems such as acid rock drainage treatment and aquifer storage and recovery. However, accurately simulating extreme cases of evolving pore space presents challenges due to the inherent heterogeneity and nonlinear reactions in a porous medium. In response, this study introduces a comprehensive model that integrates the effects of tortuosity on permeability and surface area on reactivity during oxidative precipitation of Fe(II) in a porous medium. Benchmark simulations include an innovative permeability–tortuosity–porosity model accounting for Fe precipitation, as well as the occurrence of complete clogging from localized precipitation, which leads to a reduction of permeability and outflow. The outcomes demonstrate complete pore clogging when Fe(II) concentration reaches 10 mmol/L and a significant decrease in outflow at a Fe(II) concentration of 100 mmol/L. The model’s predictions provide detailed insights into the evolution of the pore matrix during hydrogeochemical reactions and support the development of regional engineering-scale models for applications in mining, agriculture, and environmental management. Full article

Urmia Lake (UL) is the sixth-largest saltwater lake in the world; however, there is a dearth of geotechnical studies on this region. Geotechnical characteristics of a site are considered important from different engineering perspectives. In this research, the results of 255 laboratory tests and the data of 55 in situ tests were used to determine the geotechnical properties of sediment in UL. The changes of parameters in depth are presented in this study. The results indicate that compressibility, initial void ratio, water content, over-consolidated ratio (OCR), and sensitivity have larger values near the lake bed. Moreover, increasing the sediment depth leads to significant reductions in these values. According to the sediment strength analysis through the vane shear and standard penetration tests and the unit weight of sediments, there is an increasing trend caused by the increased depths of layers. Diverse applied correlations are proposed and can be used as preliminary estimates in similar types of sediments in engineering projects as well as scientific studies. Furthermore, undrained shear strength and compression index trends in depth and the Su/σ’_v Curve against OCR are compared with the literature, and the results reveal similar trends in similar sediments. The main minerals identified in these sediments include calcite, dolomite, quartz, calcium chloride, and halite. The salinity of the lake water is caused by the presence of calcium chloride and halite minerals. The Cao factor observed in chemical compounds can have a significant impact on the cohesion of the soil particles. This research provides comprehensive information on the geotechnical characteristics of UL. Moreover, the results of this study show that UL Sediments are soft and sensitive, especially in shallow depths, and they contain a significant amount of organic content; therefore, it is recommended to use suitable improvement methods in future geotechnical and structural designs. This study and similar surveys can help prepare the groundwork for designing safer marine structures. Full article