Search Results (281)

Probabilistic slope stability analysis requires tools that are both computationally efficient and accurate for uncertainty propagation. This study develops a reliability-oriented surrogate framework coupling a multilayer perceptron artificial neural network with particle swarm optimization (ANN–MLP–PSO). The model was trained on 2014 homogeneous slope cases drawn from literature records and mechanics-based simulations. PSO identified a best-performing six-hidden-layer architecture achieving a coefficient of determination of R² = 0.95 on the held-out test set. The trained surrogate was embedded in a probabilistic sampling framework to estimate the probability of failure (P_f), reliability index (β), and factor-of-safety quantiles, then applied to the Mansourieh slope near Beirut, Lebanon, under dry and wet conditions. Outputs were benchmarked against the First-Order Second-Moment method (FOSM), the Point Estimate Method (PEM), and Monte Carlo simulation (MCS). The comparison showed that the ANN–MLP–PSO surrogate reproduced the dry-to-wet changes in factor-of-safety distributions, probability of failure, and reliability index obtained from the conventional reliability methods under the same probabilistic assumptions, with wet-scenario failure probabilities ranging from approximately 86% to 99%. Despite quantitative differences, all four methods identified the same reliability trend and engineering interpretation. Once trained, the surrogate enabled rapid probabilistic evaluation without repeated deterministic calculations, providing an efficient tool for slope stability screening and uncertainty-aware geotechnical decision support. Full article

Ground-motion intensity measures (IMs) are key parameters for seismic hazard and risk assessment. However, seismic hazard characterization and code-based design spectra commonly rely on a limited set of parameters, particularly peak ground acceleration (PGA), spectral acceleration, and control periods defining spectral shape. Such representations may not fully capture seismic input relevant to structural response, soil deformation, slope instability, and indirect environmental impacts. This study analyzes 220 horizontal accelerogram components recorded during the Vrancea earthquakes of 4 March 1977, 30 August 1986, 30 May 1990, and 31 May 1990. Twenty-three IMs were computed, covering peak and effective amplitudes, velocity-related measures, cumulative and energy-based indicators, spectral intensities, duration, cyclicity, and impulsivity, together with a set of frequency content-related parameters. Pearson and Spearman correlations were evaluated using both the geometric mean and the maximum of the two horizontal components. Hierarchical clustering, PGA-centered correlation profiles, event-specific comparisons, and spatial representations were used to assess redundancy, complementarity, and relationship stability. Results show that amplitude-, velocity-, and spectrum-related IMs form strongly correlated groups, whereas duration, cyclicity, and impulsivity remain more distinct. Spatial comparisons also show that different IMs may produce different station rankings and regional patterns for the same event. These findings support selecting complementary IM families for more comprehensive, risk-informed structural and geotechnical applications. Full article

Landslides in weathered gypsum deposits present significant geotechnical challenges because progressive weathering, groundwater fluctuations, and residual strength degradation strongly influence slope stability. This study investigates the failure mechanism and remediation of a large translational landslide in weathered gypsum deposits in Çankırı, Türkiye. An integrated engineering geological assessment was conducted using data from 16 boreholes, laboratory tests, and groundwater/inclinometer monitoring records, followed by residual shear strength back-analysis and slope stability evaluation. A three-dimensional geological model was developed, and cross-sections were analyzed using the Morgenstern–Price limit-equilibrium method. Back-analysis identified residual shear strength parameters of c′ = 7.5 kPa and ϕ′ = 10° for the weathered gypsum, while laboratory direct shear tests yielded c′ = 4.0 kPa and ϕ′ = 9.9°. The friction angles obtained from the two approaches are nearly identical, whereas the back-calculated cohesion is slightly higher than the laboratory-derived value. Back-analysis parameters were used to design remediation measures, including slope unloading, rock buttress construction, toe fill improvement, and surface/subsurface drainage. Stability analyses increased the factor of safety to 1.76 under static loading, while pseudo-static analyses satisfied the recommended seismic design criterion (FS ≥ 1.10). Equivalent-linear Newmark analyses predicted a permanent displacement of 15 cm, within acceptable limits. The methodology provides a practical framework for assessing and stabilizing landslides developed in weathered gypsum deposits in seismically active regions. Full article

Clay slopes are particularly sensitive to variations in soil strength, groundwater conditions, and slope geometry, making their rapid and reliable assessment essential for geotechnical design, landslide prevention, and infrastructure risk management. This study develops and evaluates an empirical express method for estimating the stability of clay slopes based on the relationship between soil mechanical parameters, slip surface geometry, and the factor of safety. The proposed approach derives empirical dependencies for the radius of the potential circular slip surface and the coordinates of its centre as functions of slope height, cohesion, internal friction angle, and water-related conditions. The method is supported by long-term field observations and geotechnical investigations of clay slopes, including dry and water-affected scenarios. Two representative stability conditions are considered: dry slopes and slopes influenced by an elevated depression curve. The method was evaluated for 45° clay slopes with heights up to 60 m, using eight representative cases: four dry scenarios and four water-affected scenarios. The calculated factors of safety were compared with GEO5 SLOPE results obtained using Bishop’s simplified method. The comparison showed that most analysed cases presented differences below 5% between the proposed express method and the Bishop-based numerical benchmark, with larger deviations occurring only in selected boundary cases. The results demonstrate that the proposed method can provide a rapid preliminary assessment of clay slope stability, supporting early-stage geotechnical diagnosis, risk screening, and decision-making in regions where clayey formations and slope instability are recurrent. Full article

Slope stability assessment remains a fundamental challenge in geotechnical engineering because of the complex nonlinear interactions among soil properties, slope geometry, and hydraulic conditions, particularly variations in pore-water pressure. This study investigates the reliability of Artificial Neural Network–Multi-Layer Perceptron (ANN–MLP) models for predicting the Factor of Safety (FoS) of homogeneous soil slopes through a systematic comparison of three gradient-based optimization algorithms: Adam, Mini-Batch Gradient Descent (MBGD), and Nesterov Accelerated Gradient (NAG). A database comprising 2014 slope cases, compiled from published studies and numerically generated using Limit Equilibrium Method (LEM) and Finite Element Method (FEM) analyses, was used for model development and k-fold cross-validation. Beyond statistical evaluation, the developed models were validated using two classical dry-slope benchmark frameworks based on the Taylor stability charts and Bishop–Morgenstern stability coefficients, followed by two documented engineering case studies from Hulu Kelang and Pahang, Malaysia, to assess predictive performance under both dry and variable hydraulic conditions. Adam achieved the highest cross-validated predictive accuracy (R² = 0.988; RMSE = 0.212), whereas MBGD demonstrated the closest overall agreement with the reference LEM solutions across the validation cases and under increasing pore-water pressure ratios. NAG generally produced more conservative predictions while exhibiting greater sensitivity to hyperparameter selection. All models successfully reproduced the expected nonlinear reduction in FoS with increasing pore-water pressure, consistent with established geotechnical behaviour. The results demonstrate that optimizer selection significantly influences ANN–MLP prediction behaviour and that properly validated gradient-based ANN models can serve as efficient decision-support tools for rapid slope stability assessment under hydraulic variability. Full article

Transparent soil technology (TST) provides a non-intrusive visualization approach for geotechnical model experiments by matching the refractive indices of transparent particles and pore fluids. This review systematically examines recent advances in TST, from material preparation to measurement methods and engineering applications. The preparation of transparent sand and transparent clay, pore-fluid matching, degassing treatment, and mechanical similarity with natural soils are summarized. The development of optical measurement and image analysis methods, including laser slicing, particle image velocimetry, digital image correlation, speckle imaging, and three-dimensional reconstruction, is then discussed to clarify the transition of TST from qualitative observation to quantitative full-field deformation measurement. Bibliometric keyword evolution further indicates that research has shifted from early material feasibility toward engineering-oriented applications and intelligent visualization. Current applications in pile–soil interaction, tunneling, slope instability, seepage, and erosion demonstrate the value of TST for revealing displacement-field evolution, strain localization, seepage-path development, particle migration, and shear-band propagation. Remaining challenges include limited mechanical similarity, optical stability, large-scale applicability, and efficient data processing. Future work should emphasize standardized material systems, high-resolution three-dimensional visualization, multiphysics coupling, and integration with artificial intelligence. Full article

Resource-based cities in Northwest China face increasing ecological, geotechnical, and socio-economic challenges caused by long-term mining, including subsidence, slope instability, waste rock accumulation, soil erosion, industrial decline, and settlement deterioration. Post-mining land reuse is constrained by geological safety, foundation stability, slope safety, drainage capacity, erosion risk, and waste rock dump stability, yet existing restoration studies often separate engineering remediation from landscape reuse, industrial pathway selection, and long-term governance. Taking a mining area in City A, Gansu Province, as a case study, this paper develops a geotechnical constraint-based ecology–landscape–economy framework for post-mining land reuse and sustainable human settlement improvement. Unlike conventional reclamation approaches that mainly emphasize engineering remediation, vegetation recovery, or single-function land reuse, this study integrates geotechnical constraints, land-unit classification, pathway-specific compatibility assessment, and capital–space coupling into a planning-scale decision-support framework. Post-mining land was classified into five units, and their compatibility with three restoration plus industrial pathways was assessed using five indicators: geological safety, ecological sensitivity, land-use availability, landscape and cultural value, and industrial operation potential. The results indicate that backfilled mining voids and reclaimed platforms are most suitable for modern agriculture, tailings ponds and subsidence waterbodies for cultural tourism and wellness, and waste rock dump platforms and other stable, low-sensitivity open land for new energy development. A capital–space coupling mechanism is further proposed to link restoration, support, and development zones with government funds, corporate capital, social capital, green finance, and industrial income. This framework provides a planning-scale engineering-suitability screening tool for sustainable post-mining land transformation. Full article

Urban hillside areas concentrate hydrological and geotechnical risks intensified by accelerated urbanization and climate change. Although Nature-Based Solutions (NbS) are increasingly recognized as promising strategies for urban resilience, their application in hillside environments remains limited in scientific literature. This study integrates bibliometric analysis and a Systematic Literature Review (SLR) based on searches conducted across Scopus, ScienceDirect, and Web of Science from 2020 to 2025. Of the 4435 retrieved publications, only 92 addressed the association between NbS, hydrological modeling, and urban hillside environments. This reduction suggests that research integrating these themes remains limited within the adopted search criteria. The results demonstrate that hillside occupation in the Global South is conditioned by socio-spatial inequality, increasing exposure to landslides, erosion, and hydrological hazards. NbS were shown to reduce runoff peaks and contribute to slope stabilization when strategically positioned and adapted to slope gradient and hydrological connectivity; however, their effectiveness depends on continuous maintenance and monitoring. Comparative assessment indicates that most hydrological models are still applied in isolation, limiting the representation of coupled infiltration, soil saturation, and subsurface instability processes. The results indicate that effective NbS implementation in urban hillside areas requires integrated modeling approaches, interdisciplinary frameworks, and risk-oriented urban planning, particularly in socio-environmentally vulnerable contexts. Full article

Sustainable landslide hazard mitigation requires scenario-based assessment of nature-based solutions under realistic hydromechanical and multi-hazard conditions. This study evaluates the mechanical effect of Vetiver grass (Chrysopogon zizanioides) on slope stability in Loja, southern Ecuador, through an integrated framework combining geotechnical characterization, direct shear testing, finite element modelling, limit equilibrium analysis, and targeted statistical evaluation. Three fine-grained soils, classified as CH, MH, and ML, were analysed under baseline groundwater conditions, groundwater with an 8 kN/m² surcharge, and groundwater with surcharge plus pseudo-static seismic loading. Vetiver reinforcement increased apparent cohesion by 8.92–27.65% and internal friction angle by 6.90–17.43%, with the highest cohesion gain in ML soil. Numerical results showed that stabilization was controlled by soil type, slope geometry, loading condition, and interaction between the 2.0 m root-reinforced layer and the governing failure mechanism. Under surcharge loading, FS for ML at 0.5H:1V increased from 1.056 to 1.450. Under combined loading, FS increased from 0.217 to 1.440 for ML at 1H:1V and from 0.587 to 2.060 for CH at 1H:1V. Targeted ANOVA/MANOVA for MH soil confirmed the influence of geometry and combined loading. Therefore, Vetiver should be considered a complementary, site-specific, and risk-informed mitigation measure rather than a universal stabilization solution. Full article

This paper assesses mining-induced surface deformation in Mine-A of the Khetri Copper Belt, India, using a three-dimensional (3-D) numerical model based on geological, geotechnical, mine layout, and in situ stress data. 3-D numerical models were developed for the virgin state, current mining state, next 5 years of mining, and next 10 years of mining, and their corresponding strain and displacement were analysed in different directions. For the mine lease boundary, the strain increment from the virgin to current mining state shows maximum surface strain of 2.41 mm/m, 1.93 mm/m, and 2.35 mm/m in the XX, YY, and ZZ directions, respectively, and the displacement increment from the virgin to current mining state shows maximum surface displacement of 0.003 m, 0.002 m, and 0.003 m in the X, Y, and Z directions, respectively. The results indicate that the model-predicted surface deformation response for the current, next 5 years, and next 10 years of mining states is mainly concentrated around already disturbed zones, while the incremental deformation outside such zones remains comparatively limited under the simulated mining sequence. The spatial concentration of deformation within the mining-influenced zone is further supported by available Total Station monitoring data. From a mine planning perspective, the validated modelling framework is useful for identifying locations requiring focused subsidence monitoring, slope stability assessment, and future model refinement. Full article

The stabilization of public infrastructure on active volcanic slopes presents significant geotechnical challenges, particularly in coastal regions exposed to extreme hydrological stressors. This paper presents a forensic diagnosis and the structural rehabilitation of the Porto da Cruz Cemetery (Madeira Island, Portugal), which suffered severe progressive failure following localized, shallow-founded interventions in 2004. Historical inclinometer data (2015–2022) revealed continuous deep-seated creep within the volcanic colluvium (Geotechnical Zone 2–ZG2) at rates up to 0.17 mm/day, triggered by basal fluvial undercutting. To mitigate these kinematic drivers, a systemic “Toe-to-Crest” stabilization paradigm was implemented. Following the hydraulic confinement of the slope’s lower boundary, a high-capacity deep foundation network—comprising 26 m rock-socketed micropiles and 600 kN active multi-strand anchors—was executed to bypass the failure plane and encastre directly into the competent basaltic bedrock (Geotechnical Zone 1–ZG1). The structural performance was validated through rigorous load testing and a real-time robotic Structural Health Monitoring (SHM) system. Post-construction telemetry confirmed absolute kinematic stabilization, maintained continuously throughout the critical execution phases and subsequent monitoring period (2024–2025). By integrating deep bedrock anchoring, pore-pressure mitigation, and digital telemetry, this case study validates the economic and geomechanical superiority of systemic subsurface bypass over reactive surface maintenance. Ultimately, it establishes a scalable, climate-adaptive engineering blueprint for safeguarding critical coastal heritage across Macaronesia against escalating environmental multi-hazards. Full article

Loess has a metastable microstructure and high water sensitivity. When exposed to water, it undergoes rapid structural damage and disintegration, posing significant risks to the stability and durability of geotechnical structures such as foundations and slopes. Unconfined compressive strength (UCS) tests, direct shear tests, uniaxial tensile strength tests, and slake durability tests were conducted to evaluate the treatment performance. Optical microscopy and SEM were used to characterize the changes in microstructure to explain the potential reinforcement mechanism. The results show that microbial-induced carbonate precipitation (MICP) treatment leads to substantial improvement. Compared with untreated loess, the UCS, cohesion, internal friction angle, and uniaxial tensile strength increased by 370%, 663%, 43.7%, and 480%, respectively. Empirical refinements to the Mohr-Coulomb criterion were established to relate the measured UCS and uniaxial tensile strength to their theoretical values predicted from cohesion and friction angle. Both correlation models achieved R² > 0.82, quantifying the additional structural strength contributed by bio-cementation. At the same time, the treatment significantly improved water stability, and the slaking index was reduced from 100% to less than 20%. Microstructural analysis shows that precipitated calcium carbonate crystals bond soil particles at contact points and fill inter-particle pores, constructing a bonding framework, which enhances the mechanical strength and water stability of the soil mass. These research results further illustrate the potential of MICP in enhancing the performance of loess in engineering projects. Full article

Natural fibre meshes have emerged as a promising class of sustainable geotechnical reinforcement materials; however, no calibrated and validated directional constitutive model currently exists in the scientific literature for Furcraea macrophylla (fique) fabric under contrasting hygroscopic states. This knowledge gap prevents the adoption of performance-based, reliability-centred design approaches and limits the broader use of this Andean biotextile in bioengineering practice. The present study develops, calibrates, and validates a nonlinear constitutive model integrating warp/weft fabric anisotropy, a scalar damage law (Dk), and a hygroscopic reduction factor (φh). A multiscale experimental programme—comprising SEM-EDX, FTIR-ATR, TGA, CO₂ physisorption, wide-strip tensile testing (n ≥ 5 per condition; 4 conditions × 2 directions), large-scale direct shear, and RL-CBR tests—provided all model parameters. Statistical analysis (two-way ANOVA; Shapiro–Wilk normality test; Levene homogeneity test) confirmed the significance of both configuration and moisture states on mechanical response (p < 0.001). Model validation by cross-validation (n = 12 retained series), Sobol global sensitivity analysis, and Monte Carlo uncertainty propagation (N = 1000 iterations, Latin Hypercube Sampling) yielded R² = 0.94 ± 0.03 and a normalised root mean square error (NRMSE) < 8.5% across all series; 98% of all individual experimental data points (≥60 points across 12 test series) fell within the 95% Monte Carlo confidence interval. The hygroscopic reduction factor dominated mechanical uncertainty with a Sobol first-order index of Si(φh) = 0.82, confirming that moisture-induced plasticisation governs reinforcement stability in tropical service conditions (φh = 0.62–0.78; CV = 6.4%). A technical comparison with Colombian road construction standards confirmed that fique mesh meets minimum tensile requirements for erosion control and slope reinforcement. All raw data and the constitutive model code are available upon reasonable request to ensure full reproducibility. Full article

Surface erosion of loess slopes in arid and semi-arid regions of China remains a critical geotechnical issue, requiring green and low-carbon stabilization techniques. This study investigated the effectiveness of enzyme-induced carbonate precipitation (EICP) for the surface spraying reinforcement of Q3 loess collected from a high-fill engineering site at Yan’an University. Single-factor tests, response surface methodology (RSM), surface strength tests, CT-based three-dimensional pore reconstruction, and scanning electron microscopy (SEM) were conducted to evaluate the effects of cementation solution concentration and spraying dosage. The cementation solution was prepared by mixing analytical-grade urea and anhydrous calcium chloride at a 1:1 molar ratio, and the specimens were compacted to a dry density of 1.4 g/cm³. The results showed that surface strength first increased and then decreased with increasing cementation solution concentration and spraying dosage. Spraying dosage had a more pronounced influence than cementation solution concentration; excessive spraying above 9 L/m² reduced surface strength because of the high water sensitivity of loess. Five replicate tests at the central point were conducted to evaluate experimental error. The optimal parameters were 1.5 mol/L for cementation solution concentration and 9 L/m² for spraying dosage. CT and SEM results showed that CaCO₃ precipitation filled large pores and cemented soil particles, reducing total porosity from 6.7% to approximately 4.0%. These findings indicate that EICP improves loess surface strength mainly through pore filling and particle cementation, providing guidance for the ecological protection of loess slopes. Full article

Rainfall is a critical factor inducing slope instability, and accurate prediction of the factor of safety (FOS) of slopes under rainfall conditions is of paramount importance for disaster prevention and mitigation. Conventional numerical simulation methods incur high computational costs, while individual machine learning models are often insufficient to adequately capture the nonlinear spatiotemporal evolution characteristics of multiple factors under coupled multi-physics fields. To address these limitations, this paper proposes a Transformer–LSTM prediction framework. First, a fluid–structure coupling model for rainfall-affected slopes is constructed using COMSOL, and multi-factor orthogonal experiments are performed to generate multi-dimensional time-series data. Subsequently, a Transformer–LSTM fusion deep learning model is built, in which LSTM is employed to extract the temporal dynamic characteristics of rainfall infiltration, and the self-attention mechanism of the Transformer is leveraged to enhance feature extraction and global dependency modeling of key disaster-causing factors. Experimental results demonstrate that the Transformer–LSTM model significantly outperforms traditional PSO-LSTM, PSO-SVM, and standalone Transformer or LSTM models in terms of both prediction accuracy and generalization capability. Its coefficient of determination (R²) remains above 0.94, and key evaluation metrics—including mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE)—attain the lowest values among the compared models. Furthermore, the SHAP (SHapley Additive exPlanations) interpretability framework is introduced to quantitatively elucidate the model’s predictive decision-making and to establish a physically grounded causal mapping with geotechnical mechanisms. It is confirmed that effective cohesion and slope angle exert a dominant interactive effect on the degradation of slope stability, providing data-driven support for wide-area monitoring of rainfall-induced landslides. Full article