The studied earth dam was remediated works for seepage and instability problems in the downstream area. The effectiveness of slurry cutoff walls was investigated on seepage behavior. The three-dimensional (3-D) finite element (FEM) analysis at normal high-water level (NHWL) for steady-state flow was established without and with a cutoff wall. Based on the results, the overall effectiveness of the cutoff wall was 85%, which exceeded the predicted design efficiency criterion of 75%. The embankment, residual soil, and phyllite were the three major materials that mainly intercepted by cutoff wall, with decreasing flows of 72-89%, 85-94%, and 55-94% respectively. The phyllite and quarzitic schist below cutoff wall coverage, the flows increased by 179% and 33-61%. Thus, extension of the cutoff lower tip to cover the full depth through phyllite and into the quarzitic schist is highly recommended. The cutoff wall effectiveness reduced potential wet areas on downstream area by 97%, indicating lower risk of seepage erosion. Major reductions in the phreatic line drop were observed of 12-20 m, indicated the hydraulic gradient across the wall thickness of 2.00-3.33 which are less than 4.00 against wall blowout. The piezometric heads of the existing field monitoring are higher than the model without the cutoff wall indicated the possibility of internal erosion. However, this would be clearly solved after cutoff wall construction. The estimated newly installed piezometer heads across the cutoff wall are planned. The model estimates the heads from dam axis to downstream area would lower from 160 to 140-145 m Mean Sea Level (MSL). That would certainly increase the safety on seepage and stability of the downstream slope.
Stone columns are widely used to improve soft ground, and their mechanical behavior is commonly represented by homogenized composite assumptions at the unit-cell level. However, such assumptions are often adopted without sufficient large-scale experimental validation and may not adequately capture the nonuniform load transfer, confinement-dependent friction mobilization, and drainage-sensitive nonlinear response caused by the interaction between a granular column and the surrounding soft clay. To address this issue, a series of large-scale triaxial tests was conducted on stone column-reinforced composite unit cells under static loading. The effects of area replacement ratio, confining pressure, and drainage condition on the stress-strain behavior, peak deviatoric stress, and equivalent shear strength parameters were systematically examined. Based on the test results, a modified Duncan-Chang hyperbolic model was developed, in which the area replacement ratio was explicitly incorporated into the constitutive parameters through experimental calibration. The results show that both the soft soil and the composite unit exhibit strain-hardening behavior, while the reinforced composite develops higher stiffness and strength. The peak deviatoric stress increases approximately linearly with confining pressure and replacement ratio. In addition, the equivalent cohesion changes only slightly after reinforcement, whereas the equivalent friction angle increases significantly, indicating that the strengthening effect is governed mainly by frictional enhancement. The modified model reproduces the measured stress-strain curves with good accuracy, with coefficients of determination generally above 0.90 and relative errors in peak deviatoric stress within about 10% for the tested cases. The proposed framework provides a practical constitutive description for stone column composite unit cells and a useful basis for geotechnical analysis and design.
Grouting is an essential technique for managing settlement and rectifying uneven subsidence in construction. Despite its significance, determining grouting parameters primarily relies on empirical experience, resulting in a lack of systematic and scientifically grounded methodologies. Thus, it is crucial to utilize numerical calculation methods to evaluate the effectiveness of grouting under various conditions. The calculation outcomes indicate that the formation pressure and grouting duration are critical factors that influence the expansion of the grout material. Notably, the relationship between formation pressure and the extent of grouting reinforcement displays an exponential pattern while it is inversely proportional to the reinforcement range. Building upon these analytical results, a comprehensive design framework for grouting schemes is proposed to enhance the uniformity and effectiveness of the grouting intervention. This approach optimizes the grouting process and contributes to the built environment's overall stability and structural integrity.
This study systematically investigates the compressibility of dredged clay with high water content using Portland cement (PC) and sodium silicate (SS) as composite stabilizers. The effects of SS content (0%, 3%, 6%, 12%) and curing time (3 hours, 7 days, 28 days) on compression behavior of PC-SS-stabilized specimens with the same PC content of 10% were investigated via one-dimensional consolidation tests, with microstructural evolution analyzed using SEM. Results show that PC-SS-stabilized soil exhibits significantly reduced compressibility compared to untreated soil. The e-lgp curve became bilinear, with a yield stress (p(y)) as the turning point, compressibility was low beforepy and increased markedly after. Compression indices (C-e, C-c) of stabilized soil were lower than those of untreated soil, initially decreasing and then increasing with SS content, reaching minima at 6%. The swelling index (C-s) was also the smallest at this content. Yield stress increased rapidly, then slightly decreased with SS addition, peaking at 6%. Longer curing time increased yield stress, most notably within 7 days, reduced porosity, and decreased compressibility. After 28 days, compression curves shifted upward. Microstructural analysis indicated that at 6% SS and 10% cement, continuous cementitious products formed, filling pores and cementing particles, thereby enhancing compressive performance.
Underground power distribution cables are typically installed using multi-conduit systems, in which the minimum spacing between adjacent conduits is prescribed primarily for electrical and thermal safety. However, such considerations are less critical for medium-voltage distribution systems and do not reflect the geotechnical behavior of closely buried conduits. This study presents a full-scale laboratory investigation to evaluate how conduit spacing affects soil-structure interaction and mechanical response under static and repetitive loading. Two configurations, a conventional spaced arrangement and a non-spaced arrangement, are constructed in a large instrumented soil chamber. Miniature cone penetration tests are conducted prior to loading to verify that the prepared backfill satisfied the target compaction level. Measurements of vertical soil pressure and conduit deformation reveal clear behavioral differences between the two configurations. The non-spaced configuration shows stress redistribution behavior consistent with the formation of a continuous arching mechanism, which is associated with reduced deformation under both static and cyclic loading. In contrast, the spaced configuration develops localized arching above individual conduits and exhibited greater deformation accumulation during repetitive loading. Supplemental uniaxial compression testing confirms that the stress levels mobilized in the full-scale experiments remain well within the elastic range of the polyethylene conduit, indicating minimal risk of structural yielding regardless of spacing. Overall, the results indicate that eliminating spacing does not compromise structural safety and produces favorable stress redistribution and deformation responses under the tested installation conditions. These findings suggest the need for further geotechnical evaluation of configuration requirements in medium-voltage distribution conduits.
Bentonite clay is frequently utilized in combination with sand as an effective barrier material for sealing and preventing the migration of contaminants in geo-environmental projects. This study investigates the impact of lead and copper nitrate contamination under varying pH levels and exposure durations on the geotechnical and mineralogical properties of bentonite, as well as the strength behavior of a sand-bentonite mixture with 20% bentonite content. To this end, changes in the pH and Atterberg limits of bentonite contaminated with the aforementioned pollutants were examined at initial pH values of 3, 4, and 6 over exposure periods of 0, 7, 14, and 28 days. X-ray diffraction (XRD) analysis was performed on contaminated bentonite samples to explore the correlation between the altered geotechnical behavior of the bentonite [the primary reactive component of the soil mixture] and its mineralogical changes. The results indicated that the presence of heavy metal contaminants lowered the soil pH, thereby increasing its acidity. Furthermore, as the soil acidity increased, the plasticity index (PI) decreased, with lead exerting a more pronounced effect on this reduction. Unconfined compressive strength (UCS) tests revealed that samples exhibited lower strength in more acidic environments; however, both the type of heavy metal and the resulting acidity levels influenced the magnitude of strength reduction. Finally, XRD analysis demonstrated that heavy metal contamination can alter the mineralogical composition of bentonite, with lead showing a significantly more substantial impact compared to copper.
In this research, the similar materials of rock that could be used to construct a large-scale test model by using pouring method were investigated using the orthogonal experimental design, and a model of anchored rock slope containing a weak layer was poured for the first time by casting a specimen followed by excitation on a largescale shaking table. By doing so, the shear effects on two anchorage interfaces of a rock slope containing a weak layer under the effect of seismic waves with different types, amplitudes, and excitation directions, and the influence of ground-motion parameters on the shear effect were investigated. The results showed that the shear effect first appeared on the grout-rock interface under seismic action, which caused deformation of the grout layer and the shear effect on the bolt-grout interface; the peak shear stresses on the two anchorage interfaces of a rock slope increased with increasing amplitude of input seismic waves and their rate of growth increased therewith; under the effect of different types of seismic waves, the shear effects on the two anchorage interfaces of a rock slope showed disparity, in which the peak shear stresses on the two anchorage interfaces were maximised under the effect of sinusoidal waves; in different directions of seismic excitation, there were also different shear effects manifest on the two anchorage interfaces: the peak shear stresses on the two anchorage interfaces when seismic waves were excited in the Zdirection alone were lower than those under seismic excitation in the X-direction alone. The influence of seismic excitation in the X and Z-directions combined on peak shear stresses on the two anchorage interfaces was closely related to the type of seismic wave input. The research revealed the anchoring mechanism of the rock slope under seismic action, which is expected to guide related theoretical research, experimental research, numerical simulation, and seismic design.
Simple drained, undrained and partially drained shear tests are frequently performed in soil mechanics laboratories. However, the test that simulates field conditions in which surface soil undergoes water infiltration followed by short-and long-term loading is rarely performed. Considering the fact, two series of tests have been performed in the present study. Series-1 replicates field conditions in which the surface layer of the soil experiences water infiltration followed by quick/sudden loading; the tests performed in this series are termed as pre-infiltration shearing tests. Whereas Series-2 replicates field conditions in which the surface layer of the soil experiences water infiltration followed by long term/slow loading and the tests performed in this series are termed as shearing infiltration tests. Water in these series was injected by reducing matric suction and conducted shearing in constant matric suction plane. The pore water pressure remained undrained in Series-1, during the shearing process, while in Series-2, it was maintained in a drained condition. The results indicated that reducing matric suction from 20 kPa to 0 kPa increased water infiltration by up to 37.5 cm(3), raised the degree of saturation by approximately 30%, and reduced peak deviatoric stress from about 28 kPa to 5 kPa. The soil behavior transitioned from dilation to compression, resulting in decreased stiffness and shear strength. Furthermore, matric suction effect on the stress path within the stress state space is examined and analyzed.
Abrasive water jet (AWJ) cutting technology is considered an effective method to assist shield tunnels in crossing reinforced concrete obstacles. In this study, experiments using AWJ to cut rebars and concrete under submerged conditions were conducted. The results showed that under submerged conditions the AWJ cutting depth of the concrete was much greater than that of the rebars. The efficient cutting parameters were as follows: a traverse speed of less than 2 m/min, standoff distance of less than 5 cm, and abrasive flow rate of 1100 g/min. The damage modes at the top, middle, and bottom of the rebars were primarily deformation wear, shear wear, and a mixture of deformation and shear wear, respectively. The order of importance of the influence of the submerged AWJ cutting parameters on the cutting depth of the rebars was as follows: the traverse speed, standoff distance, nozzle diameter, pump pressure, and abrasive flow rate. A prediction model for the cutting depth of the rebars was established, with an average absolute percentage error of about 15%. On this basis, suggestions that can provide guidance for practical engineering applications of effective AWJ-assisted cutting of reinforced concrete in shield tunneling projects are given.
The presence of fine particles can change the microstructure of sandy silts and thus affect their mechanical properties. In this study, a series of undrained triaxial tests was conducted to investigate the monotonic and cyclic behavior of sandy silts with fines content (FC) of 60%, 76%, and 92%. The different effective confining pressures (sigma(3)' = 40, 60, 80, 100, 120, and 140 kPa) and cyclic stress ratios (CSR,sigma(d)/2 sigma(3)' ' = 0.12, 0.18, 0.24, and 0.36) were considered in the experiment study. The research results showed that the undrained shear strength of sandy silts increased significantly with the increase of sigma(3)', but decreased with the increase of FC. A larger amplitude and rate of double amplitude axial strain and excess pore water pressure ratio were observed as the CSR increased. The liquefaction resistance of the sandy silts initially decreased and then increased with the increasing sigma(3)'. The lowest liquefaction resistance was found in the cases of sigma(3)' = 100 kPa. An increase in FC can delay the generation of excess pore water pressure and enhance the liquefaction resistance of sandy silts under the cyclic loading. Two quantitative relationships between the number of loading cycles to failure and the FC were established through nonlinear surface fitting, respectively, considering the different cyclic stress ratios and effective confining pressures. The research results can provide a reference for the liquefaction treatment of sandy silt foundations.
The excavation of deep foundation pits may cause surrounding strata subsidence and pipeline leakage-induced soil loss. This study used a global transparent soil pipe-soil-water coupling test system to investigate the soil penetration erosion failure process after pressurized pipe interface leakage. A numerical model was established on the EDEM-Fluent platform, integrating foundation pit stress fields and pipeline deformation to simulate soil fluidization triggered by pipeline damage. The effects of fine particle content (FPC), pipe buried depth ratio , and pipe flow rate on permeability failure were explored. Mechanisms of fine particle migration and skeleton failure were revealed via force chain network and fine particle bearing ratio evolution. Results show EDEM-API and Fluent dynamic mesh enable cross-scale finite-discrete element simulation. Soil with 15% FPC exhibits strong erosion resistance. Larger BDR and lower PFR delay erosion failure.
This paper investigates the combined buckling and bending response of sandwich plates composed of bidirectional functionally graded (BDFG) face sheets and a metallic foam core, resting on a partial elastic foundation. Unlike previous studies limited to single load types, the present work considers simultaneous in-plane axial loads (compressive/tensile) and transverse loads inducing out-of-plane bending deformation. Furthermore, multiple boundary conditions including simply supported, clamped, free, and mixed edge restraints are systematically examined to reflect realistic support scenarios. The BDFG face sheets possess material properties that vary continuously in both in-plane (x,z) directions, while the metallic foam core follows a porosity-dependent mechanical distribution. A quasi-3D shear deformation theory is employed to formulate the governing equations. The principle of virtual work is used to derive the equilibrium equations, which are subsequently solved using an analytical solution method. After validating the present formulation against benchmark results, an extensive parametric study is conducted to assess the influence of key parameters: foam porosity coefficient, bidirectional gradation indices, partial foundation stiffness and location, in-plane to transverse load ratio and the type of boundary support. Results reveal that the interplay between combined loading, foundation partialization, and edge restraints significantly alters the critical buckling load and maximum transverse deflection. The proposed model provides a robust design tool for lightweight sandwich structures in aerospace, civil, and marine engineering applications where non-uniform support and combined loading are prevalent.
A series of model tests were conducted to investigate how the bearing capacity of adjacent footings on sand varies with interference effects. The spacing ratio between adjacent footings, the embedment depth of the footings, and the relative density of the soil were selected as key parameters, and the interference effects were quantitatively analyzed using an efficiency factor defined as the ratio of the bearing capacity of adjacent footings to that of a single footing. The model ground was prepared using Han River sand with relative densities of 40% and 80%, and the tests were conducted by varying the spacing ratio between adjacent footings from 0 to 3. The results of the model tests revealed that the bearing capacity of adjacent footings on sand was greater than that of a single footing because of interference effects. For all the test results, both the bearing capacity and the efficiency factor reached their maximum values at a spacing ratio of approximately 0.5 and then gradually decreased with increasing spacing ratio. In addition, the bearing capacity of adjacent footings generally increased with increasing footing embedment depth and soil relative density. The trend of the efficiency factor with respect to the spacing ratio between adjacent footings in this study showed overall agreement with previously reported results. The findings of this study are expected to provide fundamental data for establishing rational footing layouts that consider the effects of interference in the design of shallow foundations on sand.
Dynamic Compaction (DC) is a widely adopted ground improvement technique, particularly effective for granular soils. This study presents a hybrid approach combining fuzzy logic implemented via a Sugeno Inference System and Particle Swarm Optimization (PSO) to estimate and enhance the effective depth of DC. A fuzzy model was developed to evaluate the influence of key operational parameters, including tamper weight, drop height, radius, number of drops, grid spacing, and soil resistance. A symbolic regression-based correlation was proposed to estimate the improvement depth and was validated against the fuzzy model results. Parametric analysis revealed that the interaction between tamper weight and drop height is the most influential factor. Optimization using PSO resulted in a 33% increase in the maximum improvement depth without additional energy input. In addition, optimal design parameters were identified, including a tamper radius of 1.5-2.0 m, 25 drops per point, and a grid spacing of 6-7 m. This hybrid AI-based framework offers a practical alternative to conventional empirical DC design and demonstrates promising capability for improving design efficiency and parameter selection.
In this work, a novel single-variable parabolic shear deformation beam theory (SPSDBT) is employed to examine the mechanical response of advanced composite sandwich beams with homogeneous isotropic core materials. The proposed approach is based on a new high-order model in which the displacement field is optimized over other existing high-order shear deformation beam theories (HSDBTs), as it is formulated with fewer unknowns than those required in the classical Euler-Bernoulli beam theory. The axial displacement field is modeled using cubic polynomial functions with respect to the thickness coordinate, enabling a precise presentation of transverse shear deformation effects. Four types of advanced composite sandwich beams are examined, incorporating both hard and soft isotropic cores. The mechanical properties of the face sheets are assumed to vary gradually through the thickness direction according to the volume fraction of the constituents, whereas the core is made of a homogeneous material (either ceramic or metal). The governing equations are systematically derived from Hamilton''s variational principle and analytically solved for simply supported boundary conditions via the Navier solution technique. The robustness and versatility of the proposed model are confirmed through a comprehensive numerical study, targeting both buckling and free vibration responses of sandwich beams. These simulations explicitly account for transverse shear deformation effects and assess the influence of various parameters, such as the material gradient index and the lengthto- thickness ratio, on the non-dimensional natural frequencies and critical buckling loads. The numerical computations were compared and showed excellent agreement with those obtained from alternative higher-order shear deformation beam models, thereby, validating the accuracy of the proposed theory.
This study presents a system reliability analysis of a gravity retaining wall (R-Wall) subjected to varying seismic conditions using a sequential compounding method integrated with deterministic and artificial intelligence approaches. Three primary failure modes, sliding (SL), overturning (OT), and bearing capacity (BC), were evaluated under five horizontal seismic coefficients K-H = 0.1 to 0.18) through deterministic analysis and validated using Artificial Neural Network (ANN) models. index (beta), calculated using the First-Order Second Moment (FOSM) method, revealed that overturning is the most critical failure mode, with beta declining sharply beyond K-H = 0.12. In contrast, SL. and BC retained relatively higher beta values (9.38-4.46 and 13.45-6.87, respectively). The overall beta(system) decreased drastically from 5.99 to 0.13, indicating increasing structural vulnerability under stronger seismic loads. ANN models with architectures 4-15-1 (SL and OT) and 7-15-1 (BC) showed excellent predictive performance (R-2 > 0.999 , RMSE < 0.005), closely replicating deterministic and system reliability outcomes. Monotonicity analysis further quantified the influence of input parameters on wall stability, highlighting K and as dominant contributors, while gamma(b) had minimal effect. Across all cases, the ANN model effectively captured complex nonlinear relationships, offering valuable insights for optimized and safer design of retaining structures under seismic loading.
The presented study attempted to propose enhanced rainfall-induced landslide susceptibility mapping method by using the Deep Feedforward Neural Network (DFNN) which is developed for analysis the non-liner feature detection in landslide susceptibility analysis. To evaluate our approach, a comprehensive dataset of triggering factors was compiled, encompassing historical landslide occurrences with total of 107 records, rainfall data, geological information, seismicity, human-activities, and topographic attributes. Through rigorous training and testing procedures, the DFNN demonstratedsuperior ability for generalization and superior performance. The effectiveness of the selected method is demonstrated on the data from the Zanjan County, known for its diverse geographical, geological, and hydrological characteristics, which are pivotal factors in mapping of landslide susceptibility. Results showcased a substantial enhancement in the accuracy of mapping of rainfall-induced landslide susceptibility for the Zanjan County, which is compared with benchmark learning classifiers. According to the results of the study, it appeared that the northeastern and southwestern area of the Zanjan County can be deemed to have a high to very-high risk of landslide occurrence, which is validated via benchmark classifiers. The western part of the Zanjan County was observed to have a very low to low risk.
To address the limitations of Gaussian process regression (GPR) in predicting ground surface settlement induced by foundation pit dewatering, namely inadequate predictive accuracy, limited generalizability, and reliance on empirical kernel selection, this study proposes a novel predictive framework, FOA-GPR. The model employs the fruit fly optimization algorithm (FOA) to optimize the weight allocation of a composite kernel comprising radial basis function (RBF) and Mat & eacute;rn kernels, thereby capturing complex, nonlinear spatiotemporal dynamics. Using six multidimensional features, including water table drawdown, cutoff curtain depth, and permeability coefficient, the proposed FOA-GPR framework is systematically evaluated against conventional machine learning models (BPNN, SVM, and GPR) as well as an Empirical Spatial Attenuation Model (ESAM). The results show that FOA-GPR delivers outstanding predictive performance, reducing the mean absolute error (MAE) by 48.2% and 76.8% relative to BPNN and ESAM, respectively, and lowering the mean squared error (MSE) by 83.8% compared with BPNN. In addition, the model achieves a high coefficient of determination (R-2) of 0.975 and improves peak probability density by 14.3% over standard GPR. Finally, Shapley Additive Explanations (SHAP) analysis indicates that water table drawdown and spatial distance to the sump well are the dominant mechanical drivers of settlement. Overall, the proposed framework demonstrates superior accuracy, robustness, and physical interpretability, offering a highly reliable tool for risk management in deep excavation projects.
This study explores the effectiveness of machine learning approaches for estimating mode-I fracture toughness (KIC) of rocks, a crucial factor in both geotechnical engineering and materials science. Six sophisticated machine learning algorithms were constructed and thoroughly assessed using a compilation of 500 experimentally acquired samples. Vital input variables such as grain size, porosity, density, water saturation, and rock classification were gathered from varied geological environments to encompass inherent diversity. The outcomes demonstrated that the Random Forest Regressor (RFR) delivered the highest average forecasting accuracy among the evaluated models. Nonetheless, the Friedman-Nemenyi statistical test showed that models like SVR and ANN exhibited similar performance levels, with no statistically significant differences within the critical difference interval. SHAP analysis additionally improved model transparency by pinpointing porosity and water saturation as the primary factors influencing fracture toughness estimates. The results also underscore the existence of complex nonlinear relationships among input features, demonstrating the capability of machine learning models to capture meaningful physical relationships in heterogeneous rock systems. By merging robust experimental datasets with cutting-edge modeling and interpretability methods, this research advances data-driven techniques in rock mechanics and offers a dependable framework for anticipating fracture behavior in intricate geological materials.
This study investigates the effects of micro-disturbance grouting on highly sensitive silt and bridge substructures through in-situ tests, theoretical analysis, and numerical simulation. A calculation method for the average volumetric strain of silt is proposed based on cavity expansion theory, and the residual displacement differences between soils and structures are interpreted. The results indicate that larger grout volumes enhance soil consolidation and reduce post-grouting displacement of both soil and bridge piers, whereas smaller volumes result in greater residual deformation. By analyzing soil responses with the effective stress principle, the displacement evolution of soils and piers can be interpreted as a three-stage process, with post-grouting displacement governed by the relationship among effective stress, pore pressure, and soil pressure. Furthermore, fluid-solid coupled discrete element simulations reveal that pore pressure in sandy soils stabilizes rapidly with distance from the injection point, while silt exhibit a cumulative effect and require longer to reach peak values. The findings provide valuable references for the design and construction of similar engineering projects.
