Search Results (136)

Zoned embankment dams are widely used because of their economic and hydraulic advantages. Yet, the stiffness contrast between the clay core and surrounding rockfill may induce transverse arching, reducing core stresses and increasing hydraulic fracturing susceptibility. This study aimed to develop explicit predictive equations for the minimum transverse arching ratio at the upstream side of the core and at the core centerline under end-of-construction conditions. A structured numerical database consisting of 288 two-dimensional plane-strain finite element analyses was generated by varying dam height, section geometry, clay-core elastic modulus, and Poisson’s ratio. Based on this database, Gene Expression Programming (GEP) and Multiple Linear Regression Analysis (MLRA) were used to derive predictive formulations. The GEP equations showed high predictive accuracy, with overall performance metrics of $R^2=0.9486$, RMSE = 0.0200, MAE = 0.0159, and MAPE = 2.9797% for $R_{min,ups}$, and $R^2=0.9644$, RMSE = 0.0163, MAE = 0.0132, and MAPE = 1.7993% for $R_{min,core}$. In both responses, normalized filter thickness emerged as the dominant variable. Compared with MLRA, the GEP formulations performed better, particularly for the upstream-side response. The proposed equations provide a practical alternative to repeated, time-consuming numerical analyses in preliminary designs and safety assessments. Full article

Reservoir water level fluctuations and rainfall drive bank slope deformation, typically exhibiting spatiotemporal lags. Existing prediction models often fail to characterize these complex coupled relationships and rely on manual variable selection, causing information loss and reduced performance. To address these issues, a novel multi-point prediction model for reservoir bank slope deformation based on lag-aware clustering (LAC), referred to as LAC-MOGP, is proposed in this study. First, the Maximal Information Coefficient (MIC) quantifies the lag between influencing factors and deformation for objective factors screening. Next, an improved dynamic time warping (DTW) algorithm with a lag-difference-constrained matching window is combined with affinity propagation (AP) to cluster monitoring points based on asynchronous temporal correlations. Finally, a DTW-based similarity weighting scheme is embedded into a multi-output Gaussian Process (MOGP) kernel to refine covariance modeling and predict deformation within each cluster. Validated using observations from the Jinlongshan slope of the Ertan arch dam, the proposed model outperformed traditional methods in prediction accuracy and long-term stability. Achieving the lowest average root mean square error (2.677 mm) and average mean absolute error (2.325 mm), the LAC-MOGP model demonstrates significant effectiveness and practical applicability for reservoir slope deformation forecasting. Full article

In the construction of conventional concrete high arch dams in high-altitude regions with large temperature variations, the prolonged and cold winters often force the suspension of concrete pouring, severely constraining the overall schedule. To address this limitation, this paper breaks away from the conventional winter-shutdown scheme by proposing a new technique: continuous construction under low-temperature conditions. It can adapt to large temperature variations, and this study develops a corresponding construction schedule simulation model for quantitative evaluation and scheme optimization. First, the influence of large diurnal temperature variations on high-altitude concrete pouring was analyzed. Based on this, a dynamic pouring technique for sub-blocks is proposed—thin-layer pouring during positive temperatures and insulation curing during negative temperatures—with the aim of transforming discrete climatic windows into a continuous construction period. Second, to accurately simulate this complex spatial partitioning and temporal scheduling process, a customized schedule simulation model based on discrete-event simulation (DES) theory was developed. The model incorporated meteorological recognition at low temperatures, dynamic dam-block partitioning, and sub-block pouring scheduling. Finally, a high arch dam on a plateau in Southwest China was used as an engineering case to compare two construction schemes: the low-temperature shutdown scheme and the continuous construction scheme. After validating the simulation model under parameter assumptions such as ideal resource availability and stable annual climate patterns, the results showed that the continuous construction scheme achieves a monthly average pouring volume of 33,721 m³ during the period with large diurnal temperature variations, which accounts for 42.48% of the average monthly pouring volume during the normal construction period. Compared to the low-temperature shutdown scheme, the coefficient of variation of the monthly pouring intensity decreases by about 40%, and the total construction period is shortened by approximately ten months. This demonstrates the potential for schedule optimization for continuous winter construction in simulation. Full article

Coal mine underground reservoirs are increasingly used for mine-water storage and reuse in ecologically fragile mining regions, but the dynamic response of artificial dam structures under coupled water-pressure and seismic loading remains insufficiently understood. This study develops a simplified two-dimensional frame-based dynamic model to compare flat slab, gravity, and arch-equivalent artificial dams. Two water pressure levels, 0.1 and 1.0 MPa, and two seismic intensities, PGA = 0.1 g and 0.5 g, were considered using four representative acceleration histories. The arch dam was represented by a vertical rectangular section with equivalent arch-action lateral restraint. Results show that water pressure primarily controls peak total displacement, whereas PGA mainly governs the dynamic displacement increment and absolute acceleration. Increasing water pressure from 0.1 to 1.0 MPa markedly amplified total displacement and tensile stress demand, while increasing PGA from 0.1 g to 0.5 g produced a clearer effect on dynamic increments than on total displacement. The arch-equivalent dam consistently showed the smallest displacement response, while the gravity-type dam developed higher tensile stress demand under high water pressure in the simplified model. Effective modal frequencies were relatively high, explaining the coexistence of small displacement demand and noticeable acceleration response. The results provide a mechanistic basis for artificial dam-type comparison and preliminary safety assessment in underground reservoirs. Full article

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