Search Results (32)

To better understand the temperature changes in face slab concrete and address challenges such as delayed curing and outdated methods in complex and variable environments, this study investigates the use of visualization and real-time feedback control in concrete construction. The conducted study systematically develops an intelligent curing control system for face slab concrete based on multi-source measured data. A tailored multi-source data acquisition scheme was proposed, supported by an IoT-based transmission framework. Cloud-based data analysis and feedback control mechanisms were implemented, along with a decoupled front-end and back-end system platform. This platform integrates essential functions such as two-way communication with gateway devices, data processing and analysis, system visualization, and intelligent curing control. In conjunction with the ongoing Maerdang concrete face rockfill dam (CFRD) project, located in a high-altitude, cold-climate region, an intelligent curing system platform for face slab concrete was developed. The platform enables three core visualization functions: (1) monitoring the pouring progress of face slab concrete, (2) the early warning and prediction of temperature exceedance, and (3) dynamic feedback and adjustment of curing measures. The research outcomes were successfully applied to the intelligent curing of the Maerdang face slab concrete, providing both theoretical insight and practical support for achieving scientific and precise curing control. Full article

To consider the influence of material parameter uncertainty on the structural deformation of a dam effectively and to establish a reasonable and reliable safety monitoring index for the displacement of a rockfill dam, a method for determining the displacement monitoring index of a rockfill dam based on stochastic finite element analysis is proposed in this paper. Firstly, uncertainty in the mechanical parameters of the rockfill material is simulated via the correlation log-normal random field, and the statistical characteristics of the dam displacement under the stability of the resultant distribution are obtained through several structural analyses, thus constructing a stochastic finite element method-based monitoring model (SFEMM model); subsequently, the boundary values of the water pressure component are determined based on the statistical characteristics of the displacement at different water levels, and the displacement monitoring index is determined by inputting it into the SFEMM model. Finally, the index is applied to the actual panel rockfill dam project. Finally, the method is applied to the actual concrete-face rockfill dam project. The results show that the SFEMM model achieves higher prediction accuracy and stability than other monitoring models, with the relative error lower than 4.7% and the correlation coefficient higher than 0.96, and the monitoring index is accurate and reasonable. This method provides a scientific and reliable new idea for the safety monitoring of rockfill dams. Full article

Deformation is a key physical quantity that reflects the safety status of dams. Dam deformation is influenced by multiple factors and has seasonal and periodic patterns. Due to the challenges in accurately predicting dam deformation with traditional linear models, deep learning methods have been increasingly applied in recent years. In response to the problems such as an excessively long training time, too-high model complexity, and the limited generalization ability of a large number of complex hybrid models in the current research field, we propose an improved multi-teacher distillation network for regression tasks to improve the performance of the model. The multi-teacher network is constructed using a Transformer that considers global dependencies, while the student network is constructed using Temporal Convolutional Network (TCN). To improve distillation efficiency, we draw on the concept of clustering integration to reduce the number of teacher networks and propose a loss function for regression tasks. We incorporate an adaptive weight module into the loss function and assign more weight to the teachers with more accurate prediction results. Finally, knowledge information is formed based on the differences between the teacher networks and the student network. The model is applied to a concrete-faced rockfill dam located in Guizhou province, China, and the results demonstrate that, compared to other knowledge distillation methods, this approach exhibits higher accuracy and practicality. Full article

Deformation predictions in high Concrete Face Rockfill Dams tend to underestimate observed settlements due to scale effect and breakage phenomena that cannot be adequately captured by laboratory tests. This paper presents a Visco-Elasto-Perfectly Plastic (VEPP) model for predicting deformations in high Concrete Face Rockfill Dams (CFRDs) that addresses these challenges incorporating explicitly key rockfill parameters like grain size and post-compaction porosity, which influence both the non-linear elastic and plastic behaviors of rockfill. The VEPP model enables deformation prediction while using standard laboratory test results. The model’s effectiveness was demonstrated through its application to the 233 m high Shuibuya Dam, the tallest CFRD in the world. The VEPP model predictions closely align with observed deformations throughout the dam’s construction, impoundment, and early operational stages. By using physically meaningful parameters, the model reduces the uncertainty associated with the empirical assessment of model parameters using back-analysis from similar projects. While the VEPP model offers improved predictive accuracy, particularly during early design phases, further advancements could be achieved by refining the creep formulation and accounting for grain size evolution during construction. This approach has the potential to optimize the design and construction of future high CFRD. Full article

The construction of high rockfill dams on deep overburden in seismically active regions poses significant challenges. Currently, there are no standardized guidelines for defining the computational domain range in seismic analysis, necessitating the establishment of a universally applicable computational domain range that optimizes the balance between computational accuracy and efficiency. This has critical engineering implications for the seismic analysis of rockfill dams on deep overburden. This study employed the seismic wave input method to consider the dynamic interaction between the dam, overburden, and infinite domain. A systematic investigation was conducted on a concrete-faced rockfill dam (CFRD) constructed on deep overburden, considering the influences of overburden thickness, dam height, overburden properties, soil layer configuration, ground motion intensity, and the frequency content of the seismic waves. The acceleration response and seismic deformation of the dam were analyzed. Subsequently, the computational domain range corresponding to various levels of acceptable engineering precision was established. The results indicated that the lateral boundary length should extend a minimum distance equal to the sum of 3 times the overburden depth and 1.2 times the maximum dam height. Additionally, the depth below the overburden–bedrock interface should extend at least 1.2 times the maximum dam height. This study provides a crucial foundation for determining the optimal computational domain range in the seismic analysis of rockfill dams constructed on deep overburden. Full article

On 6 February 2023, two major earthquakes struck Türkiye, with their epicenters in the Pazarcık (M7.7; focal depth: 8.6 km) and Elbistan (M7.6; focal depth: 7 km) districts of Kahramanmaraş city. Most of the dams in the earthquake region remained structurally safe and stable. However, 17 dams in Türkiye and 1 dam in Syria were damaged during the 2023 Kahramanmaraş earthquakes. The main objective of this study was to better understand the real seismic behaviors of the dams during the two mainshocks and significant aftershocks. An earthfill dam, a concrete-faced rockfill dam (CFRD), and a roller-compacted concrete (RCC) dam constructed in the disaster area were selected to identify the real seismic behaviors of different types of dams during strong earthquakes. Acceleration records measured at the crest, right and left abutments, and foundations of the selected dams during the 2023 Kahramanmaraş earthquakes were taken into account to determine the real seismic behavior of the dams before, during, and after the earthquakes. The results of this investigation provide valuable insights into the real seismic behaviors of different types of dams in the vicinity of fault lines during strong earthquakes. Full article

A sensitivity analysis was conducted to evaluate several factors, including dam height, bank slope gradient, water storage times, and phased panel filling, on concrete-faced rockfill dams (CFRDs). The analysis identified the three most significant factors to examine their impacts on the stress-deformation characteristics of CFRDs. The results show that the order of influence on the dam body’s stress and deformation characteristics is as follows: dam height > bank slope gradient > water storage times > panel phased construction. From the perspective of stress-deformation of the face slab, water storage times predominantly affect tensile stress, while the bank slope gradient exerts the greatest influence on compressive stress. As the bank slope gradient decreases, the panel’s lateral restraint diminishes, leading to a decrease in the panel’s extrusion efficacy. Consequently, there are notable variations in the panel’s compressive stresses. An increase in dam height correlates with escalating stress and deformation in both the dam and face slab. As the bank slope gradient decreases, the deformation of the dam and face slab, as well as the range of tensile stress of the face slab, also increase. In contrast to a single water storage scenario, the face slab has experienced greater stress and deformation during the initial impoundment under multiple impoundment conditions. Therefore, multiple water storage schemes result in reduced deflection, axial horizontal displacement, and tensile stresses both along the slope and axial in the face slab. Furthermore, the tensile area at the bottom of the face slab transitions into a compressive area. Full article

Asphalt concrete impervious facings, widely adopted as the impervious structures for rockfill dams and upper reservoirs in pumped storage power stations, typically have a multilayer structure with a thin sealing layer, a thick impervious layer, and a thick leveling bonding layer. The properties of the interfaces between these layers are crucial for the overall performance of the facings. This paper develops a model to investigate the complex interface damage behavior of the facing under static water pressure and gravity. The model considers two damage origins: one is the interface adhesion–decohesion damage, which is described by the cohesive zone model (CZM) combined with the Weibull-type random interface strength distribution, and the other is the bulk damage of each layer, described by Mazars’ model. Primarily, a comparison between numerical simulation and indoor direct shear tests validates the reliability of the CZM for the asphalt concrete layer interface. Then, the damage distribution of the two interfaces is simulated, and the characteristics of the interface stress are analyzed in detail. The interface shear stresses of the ogee sections, which have different curvatures, all show an interesting oscillation between the thin sealing layer and the impervious layer, and the interface damage at this interface exhibits high heterogeneity. Furthermore, tension stress exists in the local zones of the ogee section, and the damage in this section is significantly greater than in other parts of the facings. Full article

Since ancient times, dams have been built to store water, control rivers, and irrigate agricultural land to meet human needs. By the end of the 19th century, hydroelectric power stations arose and extended the purposes of dams. Today, dams can be seen as part of the renewable energy supply infrastructure. The word dam comes from French and is defined in dictionaries using words like strange, dike, and obstacle. In other words, a dam is a structure that stores water and directs it to the desired location, with a dam being built in front of river valleys. Dams built on rivers serve various purposes such as the supply of drinking water, agricultural irrigation, flood control, the supply of industrial water, power generation, recreation, the movement control of solids, and fisheries. Dams can also be built in a catchment area to capture and store the rainwater in arid and semi-arid areas. Dams can be built from concrete or natural materials such as earth and rock. There are various types of dams: embankment dams (earth-fill dams, rock-fill dams, and rock-fill dams with concrete faces) and rigid dams (gravity dams, rolled compacted concrete dams, arch dams, and buttress dams). A gravity dam is a straight wall of stone masonry or earthen material that can withstand the full force of the water pressure. In other words, the pressure of the water transfers the vertical compressive forces and horizontal shear forces to the foundations beneath the dam. The strength of a gravity dam ultimately depends on its weight and the strength of its foundations. Most dams built in ancient times were constructed as gravity dams. An arch dam, on the other hand, has a convex curved surface that faces the water. The forces generated by the water pressure are transferred to the sides of the structure by horizontal lines. The horizontal, normal, and shear forces resist the weight at the edges. When viewed in a horizontal section, an arch dam has a curved shape. This type of dam can also resist water pressure due to its particular shape that allows the transfer of the forces generated by the stored water to the rock foundations. This article takes a detailed look at hydraulic engineering in dams over the millennia. Lessons should be learned from the successful and unsuccessful applications and operations of dams. Water resource managers, policymakers, and stakeholders can use these lessons to achieve sustainable development goals in times of climate change and water crisis. Full article

Some important discoveries have been revealed in some studies, including that the settlement of concrete face rockfill dams (CFRDs) may cause cracks in the concrete face slabs, which may lead to dam collapse. Therefore, deformation behavior prediction of CFRDs is a longstanding and emerging aspect of dam safety monitoring. This paper aims to propose a settlement prediction model for CFRDs combining the variational mode decomposition (VMD) algorithm, long short-term memory (LSTM) network, and support vector regression algorithm (SVR). Firstly, VMD is applied in the decomposition of dam settlement monitoring data to reduce its complexity. Furthermore, feature information on settlement time series is extracted. Secondly, the LSTM and SVR are optimized by the Harris hawks optimization (HHO) algorithm and modified least square (PLS) method to mine the major influencing factors and establish the prediction model with higher precision. Finally, the proposed model and other models are applied to predict the deformation behavior of the Yixing CFRD. Prediction results indicate that the proposed method possesses particular advantages over other models. The proposed VMD-LSTM-SVR model might help to evaluate the settlement trends and safety states of CFRDs. Full article

The accurate and efficient inversion of permeability coefficients is significant for the scientific assessment of seepage safety in concrete face rockfill dams. In addressing the optimization challenge of permeability coefficients with few samples, multiple parameters, and strong nonlinearity, this paper proposes a novel intelligent inversion method based on the Sobol-IDBO-SVR fusion surrogate model. Firstly, the Sobol sequence sampling method is introduced to extract high-quality combined samples of permeability coefficients, and the equivalent continuum seepage model is utilized for the forward simulation to obtain the theoretical hydraulic heads at the seepage monitoring points. Subsequently, the support vector regression surrogate model is used to establish the complex mapping relationship between the permeability coefficients and hydraulic heads, and the convergence performance of the dung beetle optimization algorithm is effectively enhanced by fusing multiple strategies. On this basis, we successfully achieve the precise inversion of permeability coefficients driven by multi-intelligence technologies. The engineering application results show that the permeability coefficients determined based on the inversion of the Sobol-IDBO-SVR model can reasonably reflect the seepage characteristics of the concrete face rockfill dam. The maximum relative error between the measured and the inversion values of the hydraulic heads at each monitoring point is only 0.63%, indicating that the inversion accuracy meets the engineering requirements. The method proposed in this study may also provide a beneficial reference for similar parameter inversion problems in engineering projects such as bridges, embankments, and pumping stations. Full article

Concrete-face rockfill dams have gradually become the preferred dam type in the engineering community. This study presents a hydropower station in China as a case study to introduce a new type of embedded concrete-face rockfill dam. The static and dynamic stress–strain characteristics of the proposed and conventional concrete-face rockfill dams were compared, and the optimal height of the embedded concrete body at the hydropower station was determined. The results indicate that, under static conditions, the embedded concrete body could reduce deformation upstream and downstream of the rockfill body, eliminate tensile stress along the concrete-face slab slope, reduce concrete-face slab deflection, and increase the maximum deflection area to 0.47 times the dam height. The inhibitory effect of the embedded concrete body on the stress and strain of the dam body became more evident as the size of the embedded body increased. Although the embedded concrete body did not enhance the dynamic and superposed static–dynamic stress states of the embedded concrete body and rockfill, the stress and strain increase in the dynamic state were within a controllable range. Through a sensitivity analysis and considering the terrain conditions and engineering cost of the hydropower station, the height of the embedded concrete body is recommended to be 0.4 times the dam height. Full article

The deformation of concrete-face rockfill dams (CFRDs) is a key parameter for the safety control of reservoir and dam systems. Rapid and accurate estimation of the deformation characteristics of CFRDs is a top priority. To realize this, we proposed a new model for predicting the maximum face slab deflection (FD) of CFRDs, combining the threshold regression (TR) and the improved support vector machine (SVM). In this paper, based on the collected 71 real measurement data from engineering examples, we constructed an adaptive hybrid kernel function with high precision and generalization ability. We optimized the selection of the main parameters of the SVM by a particle swarm optimization (PSO) algorithm. Meanwhile, we clustered the deformation parameters according to the dam height by the TR. It significantly contributes to the accuracy and generalization of the model. Finally, a prediction model for the FD characteristics of CFRDs combining TR and improved SVM was developed. The new prediction model can overcome the nonlinear abrupt feature of the sample data and achieve high precision with R² greater than 0.8 in the final testing set. Our model is more accurate with faster convergence compared to the previous model. This study provides a more accurate model for predicting maximum face slab deflection and lays the foundation for safety control and evaluation of dams. Full article

The western region of China is rich in hydropower resources and characterized by unique geological conditions. For the construction or planned construction of high dams in this region, different types of cover layers are formed due to special geological structures, most of which are located in high seismic intensity zones. This study focuses on four different site conditions: hard ground, medium–hard ground, medium–soft ground, and weak ground. By simulating the dynamic response of concrete-face rockfill dams under near-fault earthquake excitation, the vertical settlement of the dam and the attenuation of seismic motion under different site conditions are analyzed. The research findings reveal a consistent trend where the vertical settlement of the dams progressively escalates with increasing dam height across all four site conditions. This settlement phenomenon is especially pronounced in weak ground conditions, posing a potential risk of failure. Furthermore, when subjected to near-fault pulse-type earthquake motions, the existence of weak soil layers significantly dampens the seismic forces experienced by the dam. This finding suggests that the weaker the geological conditions of the site, the more pronounced the attenuation effect of the seismic motion. Additionally, the overburden layers have a noticeable amplification effect on near-fault pulse-type earthquake motion. However, this amplification effect is not significant in weak ground, possibly due to the presence of weak soil layers restricting the propagation and amplification of seismic motion. In conclusion, these research findings have practical significance for the dynamic response of high dam construction in different site conditions in the western region of China. They provide a scientific basis for the design and construction of high dams and serve as a reference for the implementation of seismic mitigation measures and earthquake disaster prevention in engineering projects. Full article

Dam settlement monitoring is a crucial project in the safety management of concrete face rockfill dams (CFRD) over their whole life cycle. With the development of an automatic monitoring system, a large amount of settlement data was collected. To precisely predict the structural health of dams, a combined multiple monitoring points (MMP) model and a machine learning model has been developed. In this paper, based on the physical factors of the CFRD, we comprehensively analyzed the influence of water level load transfer, rockfill rheology and soil properties on the settlement during the impoundment operation period. Then, we established a space-time distribution model of the CFRD during its operation period under multiple factors. An extreme gradient boosting (XGBoost) model was used for fitting prediction, and the model was evaluated using various performance indicators. The results show that spatial parameters such as the upper filling height, rockfill thickness, panel-point distance and soil material correlate to the deformation characteristics of the rockfill dam. Taking the monitoring data of the settlement of the Liyuan CFRD as an example, the new MMP model was evaluated and used to predict the settlement of the full-section points with higher accuracy, which has certain application and popularization value for related projects. Then, to evaluate the contribution of the components of the new MMP model, the SHapley Additive explanation (SHAP) methods are used to evaluate the importance of the selected factors, and the reasonability of these factors is verified. Full article