Concrete Face Rockfill Dam Research Articles

Significance of construction sequence and the initial behaviour in concrete-faced rockfill dams

ABSTRACT Finite Element Model simulations are widely used to validate experimental and field observations. Out of these, modelling and comparing the stability of dams under various loading conditions presents significant challenges for researchers and practitioners, none more than the concrete-faced rockfill dams that are present in Australia (e.g. Cethana dam) and around the globe. A review shows that the construction sequence of such dams has not been incorporated in the initial configuration of concrete-faced rockfill dams. In this research, static analysis has been conducted for 2D and 3D finite element models of the Kotmale concrete-faced rockfill dam (CFRD) with and without the construction stage. Both 2D and 3D analysis of the case study dam using MIDAS FEA NX software and static analysis have been conducted. A linear elastic material model and a nonlinear material model (Duncan and Chang EB Model) were used to model the rockfill material. The resulting deformations were compared with the in-situ measurements to identify the accuracy of the developed cases. Results show that construction stage inclusion and the nonlinear material model agree well with the in-situ measurements, warranting the need for such advancements in Finite Element Analysis. Such an inclusion can model future settlement behaviour reasonably well, which can lead to the development of appropriate management measures.

Simulation of non-stationary ground motions and its applications in high concrete faced rockfill dams via direct probability integral method

Many high concrete face rockfill dams (CFRDs) have been constructed in earthquake-prone areas in recent years, and it is essential to evaluate the seismic safety performance of these dams considering the randomness of seismic excitation. In this paper, the relationship between the stochastic ground motion generation method and the direct probability integral method (DPIM) is established by using the number theory point selection method as the bridge. The DPIM is introduced into the field of stochastic dynamic analysis and multi-index reliability evaluation of high CFRD for the first time. First, a non-stationary stochastic excitation model at five sites is established based on the latest standard for the seismic design of hydraulic structures. Then, taking a practical project as an example, stochastic dynamic response analysis and reliability assessment based on dam crest settlement deformation and dam slope cumulative slippage are conducted by using DIPM. Finally, the influence of these two indexes on reliability is explored by drawing the equal failure probability curve. The results show that the stochastic dynamic analysis and reliability assessment framework established in this paper can provide probabilistic seismic safety assessments for high CFRDs. Sliding damage of the dam slope is more likely than the deformation damage of the rockfill from the perspective of probability.

IFC-enabled LCA for carbon assessment in pumped storage hydropower (PSH) with concrete face rockfill dams

The construction sector in China released 5.08 billion tons of CO2 in 2020, which accounted for 50.9% of national carbon emissions. With the establishment of a clean energy system, an increasing number of pumped storage hydropower (PSH) plants are scheduled to be constructed for energy storage. However, a gap remains in calculating carbon emissions for each specific building during design and later construction, considering the specific design parameters that affect these emissions. This paper provides a life cycle assessment (LCA) method for integrated carbon assessment for PSH design projects based on industry foundation classes (IFC), and the method is used to calculate the carbon emissions from each building directly at the design stage. PSH project carbon emissions are calculated by estimating the consumption of diesel, electricity and materials, together with the corresponding conversion factors. The proposed method is validated with data from real-world PSH projects and then used to analyze the carbon emissions of different buildings to determine the influence of various factors. This study could benefit future research related to the green evaluation of PSH design projects by improving carbon emission estimation based on IFC.

Dynamic Responses of Concrete-Face Rockfill Dam to Different Site Conditions under Near-Fault Earthquake Excitation

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.

Deformation prediction model of concrete face rockfill dams based on an improved random forest model

The unique structure and complex deformation characteristics of concrete face rockfill dams (CFRDs) create safety monitoring challenges. This study developed an improved random forest (IRF) model for dam health monitoring modeling by replacing the decision tree in the random forest (RF) model with a novel M5' model tree algorithm. The factors affecting dam deformation were preliminarily selected using the statistical model, and the grey relational degree theory was utilized to reduce the dimensions of model input variables. Finally, a deformation prediction model of CFRDs was established using the IRF model. The ten-fold cross-validation method was used to quantitatively analyze the parameters affecting the IRF algorithm. The performance of the established model was verified using data from three specific measurement points on the Jishixia dam and compared with other dam deformation prediction models. At point ES-10, the performance evaluation indices of the IRF model were superior to those of the M5' model tree and RF models and the classical support vector regression (SVR) and back propagation (BP) neural network models, indicating the satisfactory performance of the IRF model. The IRF model also outperformed the SVR and BP models in settlement prediction at points ES2-8 and ES4-10, demonstrating its strong anti-interference and generalization capabilities. This study has developed a novel method for forecasting and analyzing dam settlements with practical significance. Moreover, the established IRF model can also provide guidance for modeling health monitoring of other structures.

Rockfill material uncertainty inversion analysis of concrete-faced rockfill dams using stacking ensemble strategy and Jaya optimizer

Numerical simulation of concrete-faced rockfill dams (CFRDs) considering the spatial variability of rockfill has become a popular research topic in recent years. In order to determine uncertain rockfill properties efficiently and reliably, this study developed an uncertainty inversion analysis method for rockfill material parameters using the stacking ensemble strategy and Jaya optimizer. The comprehensive implementation process of the proposed model was described with an illustrative CFRD example. First, the surrogate model method using the stacking ensemble algorithm was used to conduct the Monte Carlo stochastic finite element calculations with reduced computational cost and improved accuracy. Afterwards, the Jaya algorithm was used to inversely calculate the combination of the coefficient of variation of rockfill material parameters. This optimizer obtained higher accuracy and more significant uncertainty reduction than traditional optimizers. Overall, the developed model effectively identified the random parameters of rockfill materials. This study provided scientific references for uncertainty analysis of CFRDs. In addition, the proposed method can be applied to other similar engineering structures.

Modeling the Post-construction Deformation of Spillways over Concrete-Faced Rockfill Dams

Modeling the Post-construction Deformation of Spillways over Concrete-Faced Rockfill Dams

Global sensitivity analysis of parameters based on sPCE: The case study of a concrete face rockfill dam in northwest China.

To effectively identify the key material parameters of different zones of concrete face rockfill dams and improve the efficiency of parameter optimization, a global sensitivity analysis method of parameters based on sparse polynomial chaotic expansion (sPCE) is proposed in this paper. The latin hypercube sampling method is used to select multiple groups of material parameters, and then finite element method is used to calculate the displacement of dam characteristic nodes in dam body. On this basis, the displacement is expanded by sPCE, and the polynomial basis function is reconstructed by orthogonal matching pursuit to improve the construction and analysis efficiency of the proxy model. According to the chaos coefficients, Sobol' indices are calculated to evaluate the influence of the material parameters and their interaction on different displacements of the dam. The results show that the sPCE model can accurately simulate dam displacement and its statistical characteristics with a relatively small sample size. The sensitivity of the same parameter has spatial variability, and under the influence of parameter levels and spatial distribution of different materials, the parameter sensitivity ranking of different zones has certain differences. The proposed method provides a new reference to sensitivity analysis and uncertainty analysis for practical engineering.

Dynamic evaluation method for Time-variant reliability of structural safety of Concrete-faced rockfill dam

The evaluation of the structural safety risk for concrete-faced rockfill dams (CFRDs) is susceptible to the time-varying parameters and the environments of topography, geology, and operations. Traditional evaluation methods, due to their involvement in numerical simulation, cannot meet the current requirements for intelligent monitoring in terms of timeliness and practicality. Therefore, a dynamic evaluation method of reliability in CFRDs is proposed in this paper. Due to the nonlinear mapping relationship between the time-variant reliability and the monitoring characterizations of CFRDs, the long and short-term memory neural network (LSTM) and support vector machine (SVM) models are introduced to construct the potential functional relationships between the reliability sequences and the monitoring characterizations, and the matching between the accuracy of the two models and the frequency of monitoring characterizations has been fully studied, forming an adaptive evaluation model of safety risk for the CFRDs according to the different monitoring frequencies of different monitoring items. The application of Sanbanxi CFRD shows an average relative error of less than 1% and 5% for dam slope stability and slab cracking simulations, respectively. These results demonstrate that the LSTM and SVM models with adaptive monitoring frequency exhibit high fitting and prediction accuracy and applicability, and possess theoretical and engineering application value.

Selection of efficient earthquake intensity measures for evaluating seismic fragility of concrete face rockfill dam

This study explores the crucial role of intensity measure (IM) selection for probabilistic seismic demand model development of concrete face rockfill dam (CFRD) subjected to earthquake ground motions. Nonlinear dynamic analyses are performed for CFRD with an advanced hysteretic soil model using a finite element analysis program to develop a database of earthquake-induced dam crest settlements. The numerical model is validated through centrifuge model test measurements. A selection process was carried out to evaluate the IMs based on the goodness of fit, as well as their efficiency, practicality, and proficiency. Eventually, a range of optimal IMs are selected. Conditional probability function is employed to develop fragility curves for CFRD employing both scalar and vector IMs. Five settlement ratio-based limit states are defined herein. The results show that vector fragility surfaces produce enhanced predictions of the dam damage compared with the scalar fragility curves that are most often employed.

Jaya-ICSM: A rapid inverse method driven by monitoring data for concrete-faced rockfill dams static displacement simulation

This paper presents a rapid static parameter inverse method for concrete-faced rockfill dams based on displacement data using an improved cloud surrogate model and the Jaya optimization algorithm. The improved cloud surrogate model (ICSM), which evolved from the uncertainty cloud theory, is used rapidly to establish a nonlinear relationship between static parameters and displacement. The Jaya optimization algorithm, which is proficient in recognizing the extreme value of the objective function, is selected for parameter identification. To verify the performance of the proposed method, an inverse analysis of two numerical models and a real engineering project is considered, and a comparative study with the BP neural network as the surrogate model is conducted. Study results demonstrate that ICSM has an extremely high prediction accuracy, with a mean relative error that is always under 1 %. The prediction accuracy does not increase too much even under complex nonlinear conditions or when dealing with sparse training data. Moreover, Jaya-ICSM maintains high computational efficiency throughout the entire inverse analysis, saving more than 98 % of the time compared to another inverse method and proving to be much better than direct inversion based on the finite element method. This enables real-time inverse analysis and state feedback of complex engineering. The results also illustrate that the Jaya-ICSM is promising in parameter recognition and superior in supporting the displacement evaluation of earth-rock dams. Therefore, the proposed method can be an effective tool for engineers to evaluate the safety of earth-rockfill dams and ensure their long-term stability.

Predicting the deformation behaviour of concrete face rockfill dams by combining support vector machine and AdaBoost ensemble algorithm

The accurate evaluation of deformation behaviour is very important to the optimal design and safety evaluation of concrete face rockfill dams (CFRDs). Deformation prediction is a key problem in the CFRD construction. Based on statistical review of typical deformation behaviour of 94 CFRD cases, the relationship amongst three typical deformation indexes and six influencing factors of CFRDs is analysed using multiple linear regression method. The main influencing factors of the dam behaviour are discussed. An improved support vector machine (SVM) dam deformation prediction model is proposed based on the construction of an adaptive hybrid kernel function. The particle swarm intelligent optimisation algorithm is used to determine the main parameters. To solve the problem of nonlinear mutation and discreteness of case data, the SVM-AdaBoost prediction model of typical deformation indexes is established by iterative optimisation of the basic learner composed of the improved SVM model through the AdaBoost strategy. The comparative analysis of the proposed model and existing models shows that the proposed model has good prediction accuracy and can be used to predict the typical deformation behaviour of CFRDs accurately.

Plasticity inverse analysis for Zipingpu concrete-faced rockfill dam based on advanced cloud surrogate model via improved Jaya optimization algorithm

A notable prerequisite for state assessments of earth-rockfill dams is a reasonable and accurate description of the deformation. However, due to the complexity of rockfill, its mechanical properties are often difficult to fully describe using the forward finite element method (FEM). The result of FEM depends on the constitutive model and its parameters’ selection usually obtained empirically or from indoor tests. In this paper, the improved Jaya optimization algorithm (iJaya) is combined with the advanced cloud surrogate model (ACSM) to perform inverse analysis, which has great advantages in computational speed and accuracy. The generalized plastic model (GPM) is chosen for simulation and its parameters are analyzed. Finally, the deformation field of the Zipingpu Dam is reconstructed. The results show that the ACSM can greatly replace the FEM even using GPM, achieving high prediction accuracy and reduced computation time. iJaya-ACSM can also identify the parameters of the GPM quickly and correctly. The deformation of ERDs can be well simulated based on the inverted parameters, which could help to know the state of the whole dam body. In conclusion, the proposed inverse method is promising in analyzing the deformation of ERDs.

Study on stress-deformation mechanism of concrete face rockfill dam based on centrifugal model test

The traditional method of tracking the deformation of centrifugal dam model involves burying marker points on the sidewalls, which is commonly used. However, the method is inaccurate in monitoring the deformation of the model since the constraining effect of boundary effect on the model. In this study, a quasi-distributed fiber optic monitoring system was constructed using fixed-point distributed fiber Bragg grating. Particle image velocimetry, earth pressure cell, and other electromagnetic sensors were combined to examine the rationality of the face rockfill dams centrifugal model tests. Through comparative analysis, the applicability and stability of the fixed-point distributed FBG technique in the centrifugal model test were demonstrated. It is also demonstrated that traditional monitoring methods will underestimate the deformation of face rockfill dams by 2.32 % ∼ 13.55 %. This study addresses the shortcomings of existing monitoring methods with excessive measurement errors and provides a more applicable monitoring tool for developing related experimental studies.

A Prediction Model and Factor Importance Analysis of Multiple Measuring Points for Concrete Face Rockfill Dam during the Operation Period

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.

A New Method for Inversion of Dam Foundation Hydraulic Conductivity Using an Improved Genetic Algorithm Coupled with an Unsaturated Equivalent Continuum Model and Its Application.

Seepage is a main cause of dam failure, and its stability analysis is the focus of a dam's design, construction, and management. Because a geological survey can only determine the range of a dam foundation's hydraulic conductivity, hydraulic conductivity inversion is crucial in engineering. However, current inversion methods of dam hydraulic conductivity are either not accurate enough or too complex to be directly used in engineering. Therefore, this paper proposes a new method for the inversion of hydraulic conductivity with high application value in hydraulic engineering using an improved genetic algorithm coupled with an unsaturated equivalent continuum model (IGA-UECM). This method is implemented by a new code that fully considers engineering applicability. In addition to overcoming the premature convergence shortcomings of traditional genetic algorithms, it converges faster than Bayesian optimization and tree-structured Parzen estimator inversion algorithms. This method is verified by comparing the water head from drilling exploration and inversion. The results of the inversion are used to study the influence of a cement grouting curtain layout scheme on the seepage field of the Hami concrete-face rockfill dam in China, which is used as an engineering application case of the IGA-UECM. The law of the seepage field is reasonable, which verifies the validity of the IGA-UECM. The new inversion method of hydraulic conductivity and the proposed cement grouting curtain layout in this study offer possible strategies for the design, construction, and management of concrete-face rockfill dams.

Stochastic dynamic response and seismic fragility analysis for high concrete face rockfill dams considering earthquake and parameter uncertainties

The multiple uncertainties of soil properties and ground motions significantly affect the seismic response of high concrete face rockfill dams (CFRDs). Three types of randomness (the material parameter randomness, stochastic seismic excitation, and their coupling) are generated by stochastic ground motion model and generalized F-discrepancy (GF-discrepancy) method. The generalized probability density evolution method (GPDEM) is used to analyze the influence of randomness on the stochastic dynamic response and system reliability of high CFRDs. The limit state of CFRD is defined according to the crest subsidence and the stress of face-slab, and a performance-based reliability evaluation framework is established. The results show that the randomness of ground motions dominates stochastic dynamic response of the CFRD and the dynamic reliability at different safety thresholds can be obtained by the above methods. Moreover, the proposed seismic safety evaluation framework provides a significant guidance for designing and analyzing practical engineering projects.

A finite-difference method for stress modelling based on wave propagation

SUMMARY The determinations of detailed stress states are of great importance for various environmental and engineering investigations, which makes numerical stress modelling a key issue in many fields. We developed a new stress modelling method governed by elastic wave equations using finite-difference scheme. By introducing an artificial damping factor to the particle velocity in wave modelling, the proposed method is able to solve both the dynamic stress evolution and the static stress state of equilibrium. We validate the proposed method both in body force and surface force benchmarks in different scales. With the proposed method, we are able to substantially improve the modelling accuracy of models in unbounded domain by using the perfectly matched layer as the artificial boundary conditions. A 3-D concrete-faced rockfill dam model is further presented as a numerical example of practical investigation. The consistent results with the finite-element method further illustrate the proposed method's applicability. As a minor modification to wave modelling scheme, the proposed stress modelling method is not only accurate for geological models through different scales, but also physically reasonable and easy to implement for geophysicists.

A cross-scale finite element analysis of concrete-faced rockfill dam

In this paper, a new cross-scale finite element method is developed to study the mechanical response of concrete-faced rockfill dams, in which an arbitrary-node hexahedron element is used to deal with the mesh transition between the concrete slab and dam body. By using the proposed method, the mesh sizes of concrete slab and rockfill may be very different. Moreover, since the cross-scale method doesn't change the finite element calculation framework, the proposed method is easy to use. In the simulated CFRD, the mechanical behavior of the concrete slab is described by an elastic-plastic constitutive model, and a nonlinear elastic model is applied to the rockfill materials. The computational accuracy and performance of the proposed method are analyzed. The numerical results and analysis provides an effective approach to study the local behavior of concrete face slabs.

Influence of filling sequence of concrete faced rockfill dam on deformation of squeezed sidewall and dam

During construction of concrete faced rockfill dam (CFRD), the extrusion-sidewall will be protruding or deficiency under normal. Before panel construction, local slope cutting should be taken for the squeezed side wall or supplementary filling measures should be taken after excavating the squeezed side wall, which will affect the mechanical deformation of the panel. According to the monitoring data of concrete-faced rockfill dams of some hydro-electric station in Hubei Province, the three-dimensional finite element analysis method is used to simulate the original filling sequence process of the concrete face rockfill dam. By comparing the difference between the monitoring data and the calculation results, the deformation law of the extrusion side wall and the dam is obtained, which verifies the rationality of the three-dimensional simulation analysis of the dam. The characteristic values of settlement and horizontal displacement obtained from dam monitoring and numerical calculation are compared with those of other high concrete faced rockfill dams. The characteristic values of this dam are close to those of general concrete faced rockfill dams. The deformation law of extrusion side wall and dam under two optimization schemes with different filling sequence is studied. It is found that if conditions permit, the upstream should be filled first and then the downstream to reduce the deformation of extrusion side wall to the upstream.