Search Results (132)

The primary objective of this research is to quantitatively isolate the complex driving factors of slope deformation and explicitly reveal the long-term creep mechanism induced by early excavation unloading, thereby providing a theoretical basis for long-term stability evaluation. To achieve this, this study adopts a combined approach of multivariate statistical regression and numerical simulation inversion based on long-sequence monitoring data. First, a multivariate statistical regression model incorporating time-dependent, rainfall, temperature, valley width, and excavation components was constructed to quantitatively separate the contribution weights of each factor. Second, by introducing a rock–soil creep constitutive model, a refined finite element model was established to perform back-analysis of creep parameters and numerical simulation. The results indicate that two large-scale slope-cutting excavations were the direct triggers for the deformation, resulting in shear dislocation of the deep ancient sliding zone and superficial slippage. The dominant factors exhibit distinct phasic and spatial differences: before impoundment, the time-dependent component was absolutely dominant (>80%); after impoundment, low-elevation areas were significantly affected by valley width shrinkage (>60%), while high-elevation areas remained dominated by time-dependent deformation (>74%). Numerical simulation confirmed that the nature of the deformation is “excavation unloading-induced creep along the ancient sliding zone,” and the simulation results considering creep effects accurately reproduced the actual deformation characteristics observed in situ. It is concluded that the rheological effects induced by early excavation unloading are central to the control of long-term stability. Full article

Shape optimization of arch dams is essential for balancing structural safety and economic efficiency, yet remains computationally intensive due to costly finite element analyses and strict geometric constraints. Conventional sampling techniques often yield infeasible designs that undermine surrogate model fidelity. This study proposes an integrated framework combining Stratified Conditional Latin Hypercube Sampling (SC-LHS), automated modeling, and Gaussian Process (GP) surrogate models. SC-LHS incorporates hierarchical constraints to eliminate infeasible samples during generation, while a Python-driven workflow automates the process from parameterization to simulation. Coupling the GP surrogate with NSGA-II enables efficient Pareto front exploration. The results indicate that SC-LHS is superior to standard LHS, Constrained LHS, and Sobol sequences with rejection in terms of feasibility rate and space-filling metrics. The optimal compromise solution reduces dam volume by 10.4% and tensile zone volume by 15.2% compared to the initial design. This framework effectively reconciles economic and safety objectives, offering a robust methodology for complex hydraulic structure design. Full article

Artificial dams are key retaining structures in underground coal mine reservoirs, and their mechanical performance directly affects the safety and stability of underground water storage systems. This study investigates the effects of dam type, hydraulic pressure, and top boundary condition on dam behavior using three-dimensional finite element models developed in ABAQUS. Three representative dam types, namely flat slab, gravity, and arch dams, were analyzed under three upstream water pressures (0.5, 1.0, and 1.5 MPa) and three top boundary conditions (free, simply supported, and fixed), resulting in 27 numerical cases under an overburden pressure of 4 MPa. The results show that increasing water pressure consistently increases displacement and stress in all dam types, while the deformation mode and stress redistribution strongly depend on structural form and top restraint. The flat slab dam is more prone to edge cracking and local stress concentration, the gravity dam exhibits better overall stiffness and deformation stability, and the arch dam provides more efficient stress redistribution but shows stronger edge effects under restrained conditions. Overall, the gravity and arch dams demonstrate better mechanical adaptability than the flat slab dam. These findings provide a numerical basis for dam-type selection, structural optimization, and local reinforcement design in underground coal mine reservoirs. Full article

The service behavior of polyurea used for joint sealing and seepage control in concrete arch dams is governed by complex material, geometric, and interfacial nonlinearities. This study developed a generalized interface element model incorporating damage evolution based on the nonlinear Ogden constitutive theory of polyurea materials. Using the Xiaowan Arch Dam as the engineering case, a multiple-nonlinearity coupled numerical model was established, covering the construction period, impoundment period, and temperature cycles during the operation period. The mechanical responses of surface polyurea at different locations and under varying material parameters were systematically investigated. Results show that the proposed coupled model accurately captures nonlinear contact behavior. Governed by the structural stress pattern of the arch dam, the impermeable coating is predominantly subjected to compression, while regions of high tensile stress are confined to the bottom joint areas. In seepage-control design, the coating’s restraining effect on macroscopic dam deformation can be neglected; however, dam deformation must be treated as the primary boundary condition. It is recommended that polyurea with an elastic modulus of 50 MPa and a 3 mm thickness be adopted. Blindly increasing coating thickness or stiffness may instead significantly elevate the risk of internal tensile stress. Full article

In concrete dam foundations, failure mechanisms are primarily influenced by natural rock discontinuities, the dam foundation interface, or weaker strata. This paper proposes a large displacement contact model (LDCM) based on spherical particle/surface interactions, which is computationally more robust and simpler than contact models that adopt the real block polyhedral geometry. To reduce computational costs, whenever possible, the contact interaction is defined in small displacements. The proposed LDCM is applied to a masonry arch under static loading and to the stability analysis of both a gravity dam and an arch dam. The results presented validate the proposed LDCM, and the numerical predictions are close to results obtained experimentally and closely match those obtained with a more complex polyhedral-based model. The advantages of the LDCM are highlighted, namely the decoupling of contact refinement from block refinement, which significantly reduces the computational costs for the masonry arch example. The relevance of adopting a LDCM to predict a physically accepted failure mode is emphasized for dam safety. Finaly, it is shown that the LDCM contact model can be readily adopted to assess the stability of complex dam foundation systems, with reasonable computational running times if a hybrid contact approach is used. Full article

Accurate prediction of vibration responses in hydraulic structures during flood discharge is essential for ensuring safe and stable operation. This study develops a hybrid deep learning model that combines Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory (BiLSTM), and a Channel Attention (CA) mechanism, optimized through Bayesian Optimization (BO), to predict dam gantry crane beam displacements. Time-lagged Pearson correlation and Maximum Information Coefficient (MIC) are applied to select the informative input features. The CNN-BiLSTM-CA model captures both spatial patterns and temporal dependencies in vibration signals. BO tunes model hyperparameters, while Partial Dependence (PD) analysis provides insight into how these parameters affect prediction accuracy. The model is validated using vibration data from an arch dam in Southwest China during flood discharge. Results show that CNN parameters have a greater impact on prediction accuracy than BiLSTM parameters, underscoring the importance of spatial feature extraction. Ablation studies confirm each component’s contribution. Compared with existing methods, the proposed model achieves superior accuracy with a Root Mean Square Error (RMSE) of 5.49, Mean Absolute Error (MAE) of 4.34, and correlation coefficient (R) of 99.42%. This framework provides a reliable and interpretable tool for predicting structural vibrations in hydraulic engineering under complex discharge conditions. Full article

Advancing hydropower development is crucial for supporting China’s “Dual Carbon” strategy and ensuring energy security. A key safety challenge in this endeavor is the stability of arch dam abutments under the combined action of high in situ stress and reservoir water loads. This study addresses this issue by proposing an integrated methodology that links detailed geological characterization, in situ stress quantification, and mechanical stability analysis. Using the Guxue high-arch dam as a case study, we first established a three-dimensional geological model to identify controlling discontinuities and delineate potential sliding blocks. A finite difference model was then developed to simulate the in situ geo-stress field and operational water pressures. Through stress tensor transformation, the stress state on potential slip surfaces was accurately determined, and safety factors were calculated based on the Mohr–Coulomb strength criterion. The results show that the critical left and right abutment rock blocks exhibit safety factors of 1.30 and 1.24, respectively, meeting design specifications while indicating a relatively lower safety margin on the right bank. The proposed approach, grounded in precise stress analysis, provides a reliable framework for assessing abutment stability under complex loading conditions, offering practical support for the safety evaluation and targeted reinforcement of high-arch dam projects in similar geological settings. Full article

Arch–gravity dams feature both arch action and large concrete volume, yet targeted research on temperature control and crack prevention for this type remains insufficient. To address this, a Two-Parameter Decision Chart Method for predicting allowable placing temperature, an Analytical–Numerical Hybrid Estimation Method for estimating cooling durations, and the Comprehensive Cracking Risk Index (CCRI) for assessing lifecycle concrete safety are proposed, forming a complete design methodology. A case study on a proposed project using full-process simulation quantitatively evaluates the contribution of various measures in mitigating thermal stress across dam zones. Results show that without measures, the CCRI values for interior and surface concrete reach 68.9% and 38.1%, respectively. After implementing combined optimization measures targeting the control of maximum temperature, final temperature before grouting, and internal–external temperature difference throughout the entire process, both CCRI values are reduced to zero. Contribution analysis reveals distinct zonal effectiveness: for interior concrete, low-temperature placement with first-stage cooling contributes most (59.9%); for surface concrete, second- and third-stage cooling dominates (72.7%). Therefore, in practical engineering applications for temperature control and crack prevention in arch–gravity dams, a combination of measures centered on controlling the maximum temperature, optimizing the cooling process, and enhancing surface insulation should be adopted based on the characteristics of interior and surface zones, thereby improving cracking safety. Full article

Concrete arch dams, which account for about 4% of large dams worldwide, are distinguished by their efficient geometry, economy, effective load distribution, and high storage capacity. Under thermal loads, they are susceptible to unusual behavior in terms of deflection and stresses due to geometrical peculiarities, construction methodology, and restraints, which in turn may cause potential failure. This paper analyzes the behavior of a 50-year-old double-curvature, high, thin concrete arch dam under extreme thermal loading and fluctuating water levels, using 3D linear elastic FEM analyses and monitoring data. It rigorously evaluates structural response—deflections and stresses—at salient locations and interaction zones under large temperature fluctuations, a key yet underexplored risk for thin concrete arch dams in tropical and equatorial regions. Using real monitoring data, the research also examines the effectiveness of rehabilitation measures designed to mitigate thermal impacts. Results indicate that the dam deflection reverses at extreme temperature drops and rises when the reservoir is at higher or lower levels, respectively, which is not unusual for thin concrete double-curvature arch dams. Long-term exposure to high extreme temperatures with low reservoir water levels may become a concern, as it can cause higher tensile stresses at salient points and significant dam deflections towards upstream. Full article

For arch dam seismic safety evaluation, the finite element equivalent stress method has been widely used, and existing studies have realized mature equivalent stress calculation along the foundation surface path. However, from the scientific research perspective, there is a lack of a full dam surface equivalent stress characterization method for arch dams under seismic action; from the engineering practice perspective, the traditional path method cannot fully reflect the overall stress distribution of the dam, leading to insufficient comprehensive safety evaluation. To accurately assess the impact of seismic action on the overall structural safety of arch dams and address the above limitations, this study develops a methodology for calculating equivalent stress across the entire dam surface of arch dams under seismic action. Taking a concrete arch dam as the research object, a seismic wave input method based on viscoelastic artificial boundaries is employed. Three-dimensional finite element analysis of the arch dam is performed using ABAQUS, integrated with Python-based secondary development to extract stress along the integration path of each arch ring layer and calculate sectional internal forces. The equivalent stress of each arch ring layer integration path is then processed using the material mechanics method to obtain the equivalent stress distribution across the entire dam surface. A comparative analysis is conducted between the equivalent stress on the entire dam surface and that along paths on the foundation surface regarding the seismic dynamic response and behavioral patterns of the dam. The results demonstrate that the full dam surface equivalent stress approach not only accurately captures the extreme tensile and compressive stress values in the downstream foundation area but also identifies stress extrema in the upstream dam crest region, thereby achieving comprehensive characterization of the dam stress field under seismic action and enhancing both the efficiency and accuracy of equivalent stress calculations for arch dams. This method provides more comprehensive and reliable data support for seismic design optimization and reinforcement of arch dams. Compared with the traditional foundation surface path method, the proposed method achieves 100% identification of the whole dam surface stress extremum areas, with a maximum relative error of only 1.62% in the overlapping calculation area. Full article

The measured dynamic response of concrete arch dams under seismic excitation is a typical time series that contains rich information about structural conditions. Safety monitoring based on dynamic responses of arch dam structures is highly important for the timely detection of structural damage and ensuring dam safety. In this study, a PSO-LSTM-based model for safety monitoring and damage identification of arch dam structures was proposed. The method was centered on the long short-term memory (LSTM) neural network, and key hyperparameters were adaptively tuned by the particle swarm optimization (PSO) algorithm to improve monitoring accuracy for nonlinear and nonstationary structural dynamic responses. Structural damage was identified through residual analysis combined with the 3σ anomaly detection criterion. Numerical simulations and shaking table model test cases of an arch dam were introduced for validation. The proposed method was compared with the standalone LSTM model and the SSA-LSTM model in terms of the root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R²), and damage identification accuracy. The results showed that the proposed PSO-LSTM method achieved greater accuracy in monitoring the safety of arch dam dynamic responses and effectively identified structural damage, thereby verifying its effectiveness. Full article

Cascade dams describe an arrangement of several dam structures built along a flow path. Failure of one upstream dam in the cascade system can trigger catastrophic consequences to the downstream dams, as evidenced recently in the Edenville Dam and Sanford Dam. Previous research has mainly focused on rainfall-induced dam failures, although recent failures have demonstrated a combination of floods and earthquakes. Moreover, limited studies have analyzed the sensitivity of dam breach parameters, such as dam breach height and width in dams arranged in a cascade system for seismic events. Most hydraulic simulations that model seismic-induced dam failures assume the complete collapse of dams to analyze the downstream consequences. Hence, this study presents a novel analysis in simulating earthquake-induced failures in a cascade dam system, considering the sensitivity of dam breach parameters. In addition, dam breach parameters have been derived from the structural analysis of dams employing Finite Element Models (FEMs) to a critical Peak Ground Acceleration (PGA) of 0.3 g. Two-dimensional hydrodynamic simulations, along with the full dynamic wave equations, are undertaken in the study to model the earthquake-induced cascade dam failures. The results further elaborate on the significance of modeling cascade dam failures in terms of the consecutive arrival of floods and total flow compared to individual dam failures. Sensitivity analysis of dam breach parameters shows that the breach height is more significant than the breach width and breach slope. However, its significance decreases as the dam breach flood flow path increases in distance. The study further confirms the novel utilization of structural analysis to derive dam breach parameters for seismic-induced dam failures of concrete arch dams and rockfill dams, which will guide the optimization of disaster mitigation strategies and the operational resilience of the dams. Full article

Uplift pressure is a major contributor to seismic instability in arch dam abutments, particularly where jointed rock masses form wedge-shaped failure blocks. This study develops an integrated numerical framework combining nonlinear finite element analysis, the Londe limit-equilibrium method, and Incremental Dynamic Analysis (IDA) to quantify the seismic stability of multiple abutment wedges in the Bakhtiari Arch Dam. A three-dimensional finite element model is used to compute dam–abutment thrust forces, while sixteen far-field ground motions are scaled to capture the progression of wedge instability with increasing spectral acceleration. Uplift pressures on joint planes are varied to represent different levels of grout curtain performance. The results indicate that uplift pressure is the dominant factor controlling wedge stability, substantially reducing effective normal stresses and shifting IDA and fragility curves toward lower acceleration demands. Deep wedges (WL4, WL5, WL6 located in the left abutment of the dam) exhibit the highest vulnerability, with instability probabilities exceeding 50% at spectral accelerations as low as 0.34 g under 50% uplift conditions, compared with values greater than 0.65 g for upper wedges. Parametric analyses further show that increasing the joint friction angle significantly enhances seismic resistance, whereas cohesion has a comparatively minor effect. The findings emphasize the necessity of accurate uplift characterization and wedge-specific seismic assessment, and they highlight the crucial role of grout-curtain effectiveness in ensuring the seismic safety of arch dam abutments. Full article

Concrete arch dams represent a predominant dam type in water conservancy and hydropower projects in China. The control of concrete placement progress during construction directly impacts project quality and construction efficiency. Traditional manual monitoring methods, characterized by delayed response and strong subjectivity, struggle to meet the demands of modern intelligent construction management. This study introduces machine vision technology to monitor the concrete placement process and establishes an intelligent analysis system for construction scenes based on deep learning. By comparing the performance of U-Net and DeepLabV3+ semantic segmentation models in complex construction environments, the U-Net model, achieving an IoU of 89%, was selected to identify vibrated and non-vibrated concrete areas, thereby optimizing the concrete image segmentation algorithm. A comprehensive real-time analysis method for placement progress was developed, enabling automatic ternary classification and progress calculation for key construction stages, including concrete unloading, spreading, and vibration. In a continuous placement case study of Monolith No. 3 at a project site, the model’s segmentation results showed only an 8.2% error compared with manual annotations, confirming the method’s real-time capability and reliability. The research outcomes provide robust data support for intelligent construction management and hold significant practical value for enhancing the quality and efficiency of hydraulic engineering construction. Full article

High-arch dams are usually built in high-ground stress distribution areas. The deformation and stability of the abutment slope are directly related to the safety of the construction and operation of these dams. At present, there are few studies on deformation monitoring and analysis of ultra-high-arch dam abutment slopes. In this study, the surface displacement, anchor stress, and anchor cable’s anchoring force of the dam abutment slope of Wudongde Hydropower Station before and after impounding were monitored, and the safety and deformation mechanism of the dam abutment slope were analyzed, focusing on its change amplitude and change trends. Our results indicate that surface displacement and rock mass deformation at the abutment slopes on both banks are minimal, with stability being maintained following excavation and support works and no abnormal deformation occurring during impoundment. Most anchor bolt stresses remained below 50 MPa, with stable readings exceeding 200 MPa at monitored points. The loss rates of the anchor cable’s anchorage force generally fell within ±15%, with variations primarily occurring prior to excavation and support works. Minimal changes were observed before and after impoundment, indicating overall slope stability. The deformation and stress of the dam abutment slope did not exhibit abnormal changes before or after impounding, and the entire slope is in a stable state. These research results provide a reference for the safe operation of Wudongde Hydropower Station. Full article