To address the engineering problems of road subsidence and subgrade instability in aeolian soil under traffic loads, the aeolian soil was improved with rubber particles and cement. Uniaxial compression tests and Digital speckle correlation method (DSCM) were conducted on rubber particles-cement improved soil (RP-CIS) with different mixing ratios using the WDW-100 universal testing machine. The microcrack and force chain evolution in samples were analysed using PFC2D. The results showed that: (1) The incorporation of rubber particles and cement enhanced the strength of the samples. When the rubber particles content was 1% and the cement content was 5%, the uniaxial compressive strength of the RP-CIS reached its maximum. Based on the experimental results, a power function model was established to predict the uniaxial compressive strength of RP-CIS; (2) The deformation of the samples remains stable during the compaction stage, with cracks gradually developing and penetrating, eventually entering the shear failure stage; (3) The crack and failure modes simulated by PFC2D are consistent with the DSCM test. The development of microcracks and the contact force between particles during the loading are described from a microscopic perspective. The research findings provide scientific support for subgrade soil improvement and disaster prevention in subgrade engineering.

The delayed breakage of particles significantly affects the long-term mechanical properties of rockfill materials. This study examines the effects of particle strength dispersion on the distribution of time-dependent strength using fracture mechanics and probabilistic methods. Subsequently, the distribution of normalized maximum contact force (NMCF), defined as the ratio of the maximum contact force to instantaneous strength, for specimens with uniform particle size is derived using extreme value theory and Discrete Element Method (DEM). Based on this analysis, the probabilities of delayed breakage in rockfill specimens over various time intervals are calculated using a joint probability delayed breakage criterion. The feasibility of the proposed method is validated by comparing theoretical calculation with DEM triaxial creep simulation results that accounted for particle breakage. The findings offer innovative tools and theoretical insights for understanding and predicting the particle delayed breakage behavior of rockfill materials and for developing macro-micro creep crushing constitutive models.

The main problem in expansive soil treatment with steel slag (SS) is the relatively slow hydration reaction that occurs during the initial period. To circumvent this, SS-treated expansive soil activated by metakaolin (MK) under an alkaline environment was investigated in this study. Based on a series of tests on the engineering properties of the treated soil, it can be reported that SS could enhance the strength and compressibility of expansive soil, with strength increasing by approximately 108 % for SS contents exceeding 10 % compared to 3 % lime-treated soil, and the compression index reducing by 20 %. Further addition of MK plays a dual role, enhancing strength for higher SS content while excessive MK leads to strength reduction due to insufficient pozzolanic reactions and hydration product transformation. Expansive and shrinkage behaviors are notably improved, with a 5 % increase in SS content reducing the free swelling ratio by 0.66 %-5.9 %, and the combination of 15 % SS and 6 % MK achieving a nearly 300 % reduction in the linear shrinkage ratio. Microstructural analysis confirms the formation of hydration gels, densification of the soil structure, and reduced macropores, validating the enhanced mechanical and shrinkage resistance properties of the SS-MK-treated expansive soil. Additionally, to develop predictive models for mechanical and the content of hardening agents (SS and MK), the experimental data are processed utilizing a backpropagation neural network (BPNN). The results of BPNN modeling predict the mechanical properties perfectly, and the correlation coefficient (R) approaches up to 0.98.

Different types of mass flow-like movements are often triggered by rainfall in the same mountain basin in different seasons of the year, ranging from debris flows to hyper-concentrated flows and flash floods. Despite some similarities, such as large runout and high velocity, these natural hazards are different in their propagation mechanisms. Landslide mass and materials eroded along the path may be deposited along the channel(s) and subsequently remobilised; in other cases, runoff and debris mix inside the channels or nearby the protective structures. Such combined processes are typical along the northern Italian Alps but also in steep catchments in Liguria, Campania and Calabria regions. In this work, a two-phase mathematical framework is adopted to simulate the propagation of solid and water mixtures along a 3D terrain model. The mass and momentum conservation equations are solved by including the rheological behaviour models of the materials involved: frictional for soil, Newtonian for water. Selected scenarios are presented for a case study in Southern Italy with a discussion provided on how solid concentration of flow-like mass movements evolves in a mountain catchment. Numerical results show that at first, the runoff water accumulated within the natural channels and then a debris flow propagated rapidly down the slope meanwhile the concentration of solid material decreased due to the addition of runoff water and a hyperconcentrated flow reached the foothill area, later even more diluted and capable to move several kilometres far until it almost reached a railway line.

Climate change has led to increased frequency, duration, and severity of meteorological drought (MD) events worldwide, causing significant and irreversible damage to terrestrial ecosystems. Understanding the impact of MD on diverse vegetation types is essential for ecological security and restoration. This study investigated vegetation responses to MD through a drought propagation framework, focusing on the Yangtze River Basin in China, which has been stricken by drought frequently in recent decades. By analyzing propagation characteristics, we assessed the sensitivity and vulnerability of different vegetation types to drought. Using Copula modeling, the occurrence probability of vegetation loss (VL) under varying MD conditions was estimated. Key findings include: (1) The majority of the Yangtze River Basin showed a high rate of MD to VL propagation. (2) Different vegetation types exhibited varied responses: woodlands had relatively low sensitivity and vulnerability, grasslands showed medium sensitivity with high vulnerability, while croplands demonstrated high sensitivity and moderate vulnerability. (3) The risk of extreme VL increased sharply with rising MD intensity. This framework and its findings could provide valuable insights for understanding vegetation responses to drought and inform strategies for managing vegetation loss.

The real-time monitoring of fracture propagation during hydraulic fracturing is crucial for obtaining a deeper understanding of fracture morphology and optimizing hydraulic fracture designs. Accurate measurements of key fracture parameters, such as the fracture height and width, are particularly important to ensure efficient oilfield development and precise fracture diagnosis. This study utilized the optical frequency domain reflectometer (OFDR) technique in physical simulation experiments to monitor fractures during indoor true triaxial hydraulic fracturing experiments. The results indicate that the distributed fiber optic strain monitoring technology can efficiently capture the initiation and expansion of fractures. In horizontal well monitoring, the fiber strain waterfall plot can be used to interpret the fracture width, initiation location, and expansion speed. The fiber response can be divided into three stages: strain contraction convergence, strain band formation, and postshutdown strain rate reversal. When the fracture does not contact the fiber, a dual peak strain phenomenon occurs in the fiber and gradually converges as the fracture approaches. During vertical well monitoring in adjacent wells, within the effective monitoring range of the fiber, the axial strain produced by the fiber can represent the fracture height with an accuracy of 95.6% relative to the actual fracture height. This study provides a new perspective on real-time fracture monitoring. The response patterns of fiber-induced strain due to fractures can help us better understand and assess the dynamic fracture behavior, offering significant value for the optimization of oilfield development and fracture diagnostic techniques. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

Accurate prediction of hydraulic fracture propagation is vital for Enhanced Geothermal System (EGS) design. We study the first hydraulic fracturing job at the GR1 well in the Gonghe Basin using field data, where the overall direction of hydraulic fractures does not show a delineated shape parallel to the maximum principal stress orientation. A field-scale numerical model based on the distinct element method is set up to carry out a fully coupled hydromechanical simulation, with the explicit representation of natural fractures via the discrete fracture network (DFN) approach. The effects of injection parameters and in situ stress on hydraulic fracture patterns are then quantitatively assessed. The study reveals that shear-induced deformation primarily governs the fracturing morphology in the GR1 well, driven by smaller injection rates and viscosities that promote massive activation of natural fractures, ultimately dominating the direction of hydraulic fracturing. Furthermore, the increase of in situ differential stress may promote shear damage of natural fracture surfaces, with the exact influence pattern depending on the combination of specific discontinuity properties and in situ stress state. Finally, we provide recommendations for EGS fracturing based on the influence characteristics of multiple parameters. This study can serve as an effective basis and reference for the design and optimization of EGS in the Gonghe basin and other sites. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

The joint roughness coefficient (JRC) is a key parameter in the assessment of mechanical properties and the stability of rock masses. This paper presents a novel approach to JRC evaluation using a genetic algorithm-optimized backpropagation (GA-BP) neural network. Conventional JRC evaluations have typically depended on two-dimensional (2D) and three-dimensional (3D) parameter calculation methods, which fail to fully capture the nonlinear relationship between the complex surface morphology of joints and their roughness. Our analysis from shear tests on eight different joint types revealed that the strength and failure characteristics of the joints not only exhibit directional dependence but also positively correlate with surface dip angles, heights, and back slope morphological features. Subsequently, five simple statistical parameters, i.e. average dip angle, median dip angle, average height, height coefficient of variation, and back slope feature value (K), were utilized to quantify these characteristics. For the prediction of JRC, we compiled and analyzed 105 datasets, each containing these five statistical parameters and their corresponding JRC values. A GA-BP neural network model was then constructed using this dataset, with the five morphological characteristic statistics serving as inputs and the JRC values as outputs. A comparative analysis was performed between the GA-BP neural network model, the statistical parameter method, and the fractal parameter method. This analysis confirmed that our proposed method offers higher accuracy in evaluating the roughness coefficient and shear strength of joints. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

This paper addresses the issue of crack expansion in adjacent buildings caused by foundation pit construction and develops a predictive model using the response surface method. Nine factors, including the distance between the foundation pit and the building, soil elastic modulus, and density, were selected as independent variables, with the crack propagation area as the dependent variable. An orthogonal test of 32 conditions was conducted, and crack propagation was analyzed using the FEM-XFEM model. Results indicate that soil elastic modulus, Poisson's ratio, and distance between the pit and building significantly impact crack propagation. A predictive model was developed through ridge regression and validated with additional test conditions. Single-factor analysis showed that elastic modulus and Poisson's ratio of the silty clay layer, elastic modulus of sandy soil, and pit distance have near-linear effects on crack propagation. In contrast, cohesion, density, and Poisson's ratio of sandy soil exhibited extremum points, with certain factors showing high sensitivity in specific ranges. This study provides theoretical guidance for mitigating crack propagation in adjacent buildings during excavation.

Prepulse combined hydraulic fracturing facilitates the development of fracture networks by integrating prepulse hydraulic loading with conventional hydraulic fracturing. The formation mechanisms of fracture networks between hydraulic and pre-existing fractures under different prepulse loading parameters remain unclear. This research investigates the impact of prepulse loading parameters, including the prepulse loading number ratio (C), prepulse loading stress ratio (S), and prepulse loading frequency (f), on the formation of fracture networks between hydraulic and pre-existing fractures, using both experimental and numerical methods. The results suggest that low prepulse loading stress ratios and high prepulse loading number ratios are advantageous loading modes. Multiple hydraulic fractures are generated in the specimen under the advantageous loading modes, facilitating the development of a complex fracture network. Fatigue damage occurs in the specimen at the prepulse loading stage. The high water pressure at the secondary conventional hydraulic fracturing promotes the growth of hydraulic fractures along the damage zones. This allows the hydraulic fractures to propagate deeply and interact with pre-existing fractures. Under advantageous loading conditions, multiple hydraulic fractures can extend to pre-existing fractures, and these hydraulic fractures penetrate or propagate along pre-existing fractures. Especially when the approach angle is large, the damage range in the specimen during the prepulse loading stage increases, resulting in the formation of more hydraulic fractures. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).