Bulletin of Engineering Geology and the Environment最新文献

This study evaluates the bearing capacity and liquefaction hazards in the sedimentary deposits of the Srinagar Metropolitan Region (SMR) through two novel indices: the Bearing Capacity Hazard Index (BCHI) and the Liquefaction Hazard Index (LHI). The study area is located in the Kashmir Valley, having sedimentary deposits of alluvial floodplains and Karewa highlands, which exhibit significant geotechnical variability due to their distinct depositional environments. BCHI integrates static bearing capacity (SBC), static settlement (S_S), seismic-to-static bearing capacity ratio (SBCR), and seismic settlement potential (SSP), while LHI incorporates liquefaction potential index (LPI), liquefaction settlement (S), and liquefaction severity number (LSN). These parameters have then been combined through the Analytical Hierarchy Approach integrated with a GIS platform to develop hazard maps for the region. BCHI has been used to divide the region into zones of bearing capacity hazard: low (< 0.2), medium-high (0.2–0.5), and very high (> 0.5). LHI values have been used to delineate the region based on liquefaction vulnerability: low (< 0.2), medium-high (0.2–0.5), and very high (> 0.5). Results indicate significant spatial variations in geotechnical and liquefaction hazard over the region. The alluvial plains fall in the medium-high hazard zones of liquefaction as well as bearing capacity, whereas the Karewa highlands fall in the low hazard zone of liquefaction and medium hazard zone of bearing capacity. Thereby, the study underscores the severe geotechnical risks in alluvial floodplains, while highlighting Karewa highlands as more suitable for urban expansion. The proposed hazard maps can be used for developing essential guidance for foundation design, land-use planning, and disaster risk mitigation, contributing to safer infrastructure development in the Srinagar Metropolitan Region.

Dispersive soils disintegrate rapidly when they come in contact with water thereby compromising the structures being supported. The dispersion is triggered by monovalent sodium ions found in soil pore water. Identification and stabilization of dispersive soils thus becomes imperative for the safety of the intended applications. The current study examined the performance of calcinated coal gangue (CCG) and xanthan gum (XG) in controlling the dispersivity, erosion and compressibility behaviour of dispersive soil. The dosages of CCG were maintained as 1%, 3%, 5%, 7%, and 10% respectively, whereas XG was maintained at 2%. The CCG and XG treated samples were cured for 7 and 28 days, and subjected to double hydrometer test and cylindrical dispersion test to assess the dispersivity of soil. Additionally, drip erosion test and one-dimensional incremental consolidation test were conducted. Results showed that the dispersion ratio reduced from 78% to 11% for the soil treated with 2% XG and 5% CCG. Similarly, erosion depth got reduced from 18.6 mm to 3.9 mm when treated with 2% XG and 5% CCG, thereby transforming the soil from dispersive to nondispersive. The one-dimensional consolidation test depicted that the inclusion of CCG alone increased the coefficient of consolidation (C_v) and hydraulic conductivity (k) due to non-cohesiveness, but XG addition reduced C_v and k with an increase in consolidation pressure. The microstructural examination revealed that the bonding between soil aggregations was strengthened by the XG hydrogel and filling of interaggregate voids with CCG. Considering the durability and performance of CCG and XG, the modified soil can be recommended for short term applications.

The field of engineering geology is changing rapidly in response to global pressures such as urbanization, climate change, and the growing demand for natural resources. Meanwhile, Young Engineering Geologists (YEGs), defined as early-career academics and professionals under 40 within the International Association for Engineering Geology and the Environment (IAEG), are increasingly engaged in research, training, and knowledge exchange activities. This study examines current challenges and anticipates future requirements in the field of engineering geology by integrating a quantitative analysis of journal publications from 2015 to 2025, related international projects, and feedback obtained through a survey conducted during an IAEG outreach activity. The bibliometric analysis showed a gradual shift from traditionally dominant infrastructure-focused studies toward topics such as geohazards intensified by climate change, urban planning, mitigation strategies, and sustainable development. This shift is accompanied by an increased use of digital tools, including remote sensing, data-driven analysis, and big data storage. This study also focuses on how YEG activities in research, professional development, and global knowledge exchange align with the United Nations Sustainable Development Goals (SDGs). It was found that YEG activities not only contribute to technical advancement but also to SDG 4 (Quality Education), SDG 5 (Gender Equality), SDG 10 (Reduced Inequalities), and SDG 17 (Partnerships for the Goals). Survey responses from early-career professionals point to significant demand for practical, accessible, and interdisciplinary training methodologies. Taken together, these findings highlight a pathway for how future YEG activities might be modified to address the changing requirements of the field and research directions in engineering geology.

Determining post-failure characteristics of slopes under rainfall is an essential prerequisite for assessing and mitigating landslide risks. This study proposes a coupled hydro-mechanical framework that integrates the Random Limit Equilibrium and Material Point Methods (RLE-MPM). The post-failure characteristics, landslide types and probability of slope failure considering the spatial variability of saturated hydraulic conductivity (k_s) are evaluated using this framework through probabilistic large deformation analyses. An infinite slope under rainfall and Tokai-Hokuriku expressway landslide in Japan are investigated, respectively, to illustrate the effectiveness of the proposed RLE-MPM framework. The influences of the rainfall duration as well as the coefficient of variation of mechanical parameters and k_s on the slope post-failure characteristics are investigated. Results indicate that the proposed RLE-MPM framework is computationally more efficient in evaluating the slope post-failure characteristics and probability of slope failure than the Random Material Point Method (RMPM). Additionally, the spatial variability of k_s significantly affects the means and coefficients of variation of slope post-failure characteristics. The failure characteristics of the Tokai-Hokuriku expressway landslide can be accurately predicted by using the proposed framework. This study highlights the necessity of considering the heterogeneity of soils in landslide movement prediction and risk assessment.

One of the main determinants of whether a reactivated landslide will start sliding again is the mechanical characteristics of the soil in the slip zone. Previous studies believe that the residual strength of slip zone soil is a static parameter, but many studies have found that the strength of slip zone soil will produce self-healing phenomenon, which is shown as the increase of shear strength. Based on this phenomenon, this article conducted relevant research. The healing of residual strength of the red-bed sliding zone soil under various normal stresses and consolidation time is studied through the shear-consolidation-shear test on sliding zone soil of the red-bed translational landslide, and the corresponding analysis and discussion are conducted. The findings demonstrate that the red-bed slip zone soil has a self-healing effect; the landslide’s reactivation initiation strength is between its peak strength and residual strength; the red-bed slip zone soil’s strength recovery ratio is proportional to consolidation time and inversely proportional to normal stress; and the consolidation of the slip zone soil of the red-bed translational landslides is the primary factor of the strength healing mechanism, and the mineral characteristics strengthen the mechanism to some extent. In summary, the strength healing mechanism of the red-bed slip zone soil can delay the reoccurrence of the red-bed translational landslides, and this mechanism holds significant importance for the study of red-bed translational landslides.

This study proposes a robust and efficient iterative algorithm (called iHLRF-BFGS algorithm) to find the design point of the copula-based first-order reliability method (FORM) for slope reliability analysis under incomplete probability information. First, a brief introduction to the copula theory for modeling the joint cumulative distribution function (CDF) of shear strength parameters is provided. Second, the copula-based FORM using the conventional HLRF algorithm is reviewed. Third, a novel iHLRF-BFGS algorithm for solving the copula-based FORM is derived. Finally, three cohesion-frictional slopes, namely an infinite slope, a two-dimensional (2-D) single-layered slope, and a three-dimensional (3-D) two-layered slope, are presented to illustrate and demonstrate the proposed iHLRF-BFGS algorithm. The results indicate that the iHLRF-BFGS algorithm not only demonstrates high accuracy for slope reliability problems involving explicit and implicit performance functions, but also it is more robust and efficient in finding the design point of the copula-based FORM than both first-order optimization algorithms and the HLRF-BFGS algorithm. In addition, the iHLRF-BFGS algorithm can comprehensively investigate the impact of the dependence structure of shear strength parameters on slope reliability. The prevalent use of the Gaussian copula can result in a hazardous slope design, which underscores the critical importance of proper copula selection in determining slope reliability.

The stability of the canal embankment in the Middle Route of the South-to-North Water Diversion Project is crucial to the project’s safety. However, the expansive soil widely distributed along the route tends to damage the canal embankment, owing to its strong swelling and shrinkage properties. Moreover, termite nests resulting from frequent termite activity in the region disrupt the continuity of the soil mass and exacerbate the deterioration of the expansive soil’s tensile strength, thereby posing a dual threat. Therefore, investigating the tensile strength characteristics of expansive soil in environments containing termite nests is highly relevant for engineering applications. Splitting tests were conducted on expansive soil containing termite nest pores using Particle Image Velocimetry (PIV). The test results revealed the following: The tensile strength of expansive soil decreases as the pore diameter of the termite nest increases. This is mainly because the termite nest pores reduce the effective bearing area, intensify stress concentration, and induce rapid crack propagation. The tensile strength decreases as the water content increases. The primary reason is that decreasing matric suction causes expansive soil to absorb water and swell, increases the void ratio, and substantially weakens interparticle cohesion. Based on the test results, a prediction model for the tensile strength deterioration of expansive soil was established. The findings of this study provide a scientific basis for evaluating the tensile strength of expansive soil containing termite nests, and offer important practical guidance for the later-stage, high-quality development of the Middle Route of the South-to-North Water Diversion Project.

Thermal exposure can substantially alter the hydric behaviour of carbonate stones, with direct implications for damage susceptibility and post-fire durability. This study provides a new perspective on hydric dynamics by analysing not only how water is absorbed, but also how it is retained and released after thermal exposure. Thirteen Portuguese carbonate lithologies (limestones, marbles, a breccia, and a travertine) were heated to 300 °C and 600 °C, and their hydric response was characterised through open porosity, bulk density, capillary uptake coefficients, drying rates, and total water absorption. Pore-size distribution analysis was used to assess the role of porosity and its spatial organisation in controlling these processes. Hydric susceptibility was further evaluated using time-based metrics describing the progression of both water intake and water release within each stone. Results reveal clear lithology-dependent responses, showing that thermal damage modifies pore geometry and connectivity in ways that distinctly affect both absorption and evaporation pathways. These findings deepen our understanding of thermally induced hydric behaviour and support more robust evaluations of damage susceptibility in fire-affected carbonate stones.

Lithology identification is an important basis for guiding tunnel engineering construction as well as estimating the reserves of oil, gas, and solid mineral resources. Drilling technology is one of the key methods for quickly acquiring lithological information. This paper proposes a method for identifying lithology in drilling cuttings by combining object detection algorithms with visible and near-infrared (VNIR) spectroscopy. Firstly, a laboratory VNIR spectral dataset containing 27 lithologies was established, and a classification model based on the YOLOv5s algorithm was developed specifically for identifying spectral data features in the laboratory setting. Then the field spectral data for five lithologies were collected, and the transfer learning method was employed to achieve intelligent lithology identification in field drilling cuttings. Finally, this method was applied to a real-world engineering project. The results show that the identification accuracy for laboratory lithology data is nearly 99%, with evaluation metrics reflecting the model’s excellent performance. The accuracy of the transfer learning method used for the intelligent identification of field drilling cuttings data reached 98%. In the engineering application, only one of the 30 cuttings samples was incorrectly identified, and the identification results were generally consistent with the excavation verification outcomes. The YOLOv5s object detection algorithm demonstrates good identification performance for spectral curves of different lithologies. This method holds promise for wide application in geological exploration, oil and gas resource development, and mining industries.

Most previous studies have investigated the seismic performance of subway stations in clean sands. However, naturally deposited sands are always mixed with fines, such as clay or silt. The results of laboratory tests revealed that the content of fines significantly influenced the shear modulus and cyclic liquefaction resistance ratio of the host sands. Therefore, the dynamic response and damage mechanism of the subway stations at sand-fines mixture sites deserve more attention. In this study, a series of shaking table tests were conducted to investigate the dynamic response of the subway station structure in the sand-fines mixture liquefiable sites. Different seismic motions with various intensities were applied in the shaking table tests, which represented different spectral characteristics and Arias intensities. The test results reveal that the acceleration response of a soil-structure system is sensitive to the frequency contents between 1 and 5 Hz of the input ground motions and that the excess pore water pressure ratio of the sand-fines mixture is dependent on the characteristics of its frequency spectrum and Arias intensity. Moreover, the subway station may float when the soil liquefies, and the weakest parts of the seismic resistance of the subway station structures are the center columns. These results provide reference data for the seismic design of subway stations at sand-fines mixture liquefiable sites.