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The Ground Penetrating Radar (GPR) method is a commonly used method for earth dam disease detection. However, the major challenge is that the obtained GPR image data of earth dam disease mainly relies on human judgment, especially in long-distance earth dam disease detection, which may lead to misjudgments and omissions. The You Only Look Once v5s (YOLOv5s) algorithm is innovatively employed for GPR image recognition to address the current challenge. The YOLOv5s neural network model has advantages over the traditional convolutional neural network in terms of object detection speed and accuracy. In this study, an earth dam disease detection model was established based on YOLOv5s. Raw images from actual earth dam disease detection and GPR forward simulation images were used as the initial dataset. Data augmentation techniques were applied to expand the original dataset. The LabelImg annotation tool was employed to classify and label earth dam disease, thereby creating an object detection dataset that includes earth dam disease features. The model was trained within this dataset. The results indicate that the total loss function of the model trained on the custom dataset initially decreases and then stabilizes, showing no signs of overfitting and demonstrating good generalizability. The earth dam disease detection model based on YOLOv5s achieved average precision rates of 96.0%, 95.5%, and 93.9% for voids, seepage, and loosening disease, respectively. It can be concluded that the earth dam disease detection model based on YOLOv5s may be an effective tool for intelligent GPR image recognition in identifying earth dam disease. [ABSTRACT FROM AUTHOR]

Studying the impact of mainshock–aftershock sequences on dam reliability is crucial for effective disaster prevention measures. With this purpose in mind, a new method for stochastic dynamic response analyses and reliability assessments of dams during seismic sequences has been proposed. Firstly, a simulation method of stochastic seismic sequences is described, considering the dependence between mainshock and aftershock based on Copula function. Then, a novel practical framework for stochastic dynamic analysis is established, combined with the improved point selection strategy and the direct probability integration method (DPIM). The DPIM is employed on a nonlinear system with one degree of freedom and compared with Monte Carlo simulation (MCS). The findings reveal that the method boasts exceptional precision and efficiency. Finally, the seismic performance of a practical dam was evaluated based on the above method, which not only accurately estimates the response probability distribution and dynamic reliability of the dam, but also greatly reduces the required calculations. Furthermore, the impact of aftershocks on dam seismic performance is initially evaluated through a probability approach in this research. It is found that seismic sequences will significantly increase the probability of earth dam failure compared with sequences of only mainshocks. In addition, the influence of aftershocks on reliability will further increase when the limit state is more stringent. Specifically, the novel analysis method proposed in this paper provides more abundant and objective evaluation indices, providing a dynamic reliability assessment for dams that is more effective than traditional evaluation methods. [ABSTRACT FROM AUTHOR]

This paper investigates the influence of multi-components strong motion duration on seismic performance of high concrete-faced rockfill dams (CFRDs) by fragility analysis based on the method of incremental dynamic analysis (IDA). The contributions of all compositions of earthquake excitations are considered by the definition of integrated duration based on the concept of significant duration. The nonlinear finite element model of a 2D 200-m-high CFRD is established as a case study and the vertical and horizontal displacements are selected as damage measures. Fragility curves and probabilities of two sets of 23 and 25 spectrally equivalent as-recorded bi-directional long-duration and short-duration motions are determined under different failure grades and intensities. The results show that the duration of vertical component has a certain effect on correction between strong motion duration and deformation of the dam and fragility analysis indicates that the ground motions with long duration can make more risk of failure of high CFRDs than short duration motions. Therefore, the seismic performance of high CFRDs will be reformed by taking the effect of ground motion duration into seismic design and risk assessment consideration. [ABSTRACT FROM AUTHOR]

The randomness of material parameters and earthquake excitation greatly impacts the seismic stability of high concrete-faced rockfill dam (CFRD) slopes. However, no research has comprehensively analyzed the impacts of stochastic earthquake excitations, random parameters and their coupled effects on seismic stability of CFRD slopes and selected a multi-indicator evaluation criterion to carry out performance-based safety assessment. This paper develops a novel and comprehensive framework for evaluating the seismic stability of CFRD slopes based on the generalized probability density evolution method (GPDEM) with high efficiency and accuracy. The effects of three kinds of randomness on seismic stability of CFRD slopes were comprehensively compared and analyzed on the basis of multi-indices (safety factor (F S), cumulative slip displacement and cumulative time with F S < 1.0). Firstly, the nonlinear shear strength parameters of 40 high CFRDs were statistically collected to obtain the statistical characteristics of rockfill material strength parameters of actual CFRD projects. Secondly, three kinds of random samples were generated using generalized F-discrepancy (GF-discrepancy) method and Spectral expression-Random function (SERF) method. Then, the GPDEM was introduced to combine with three indices to perform the stochastic analysis and reliability evaluation. Finally, the fragility analysis of the CFRD slope was conducted. The results reveal that F S is more sensitive to the ground motions randomness, while cumulative slip displacement and cumulative time with F S < 1.0 are more sensitive to the material parameters randomness. The seismic safety evaluation of CFRD slopes based on multiple indices with full consideration of coupled randomness effects is necessary. • GPDEM was used to perform probability and reliability analysis of the CFRD slope. • Three different random factors were considered. • Three indicators were adopted for the safety assessment of the CFRD slope. • The seismic fragility analysis of the CFRD slope was conducted. [ABSTRACT FROM AUTHOR]

Rockfill strength parameters are important indicators of the stability of a rockfill dam slope. Therefore, a rational representation of the distribution characteristics of these parameters is extremely important to accurately assess the stability of the dynamic response and reliability of the three-dimensional (3D) slope of a rockfill dam. A joint distribution model of the rockfill strength parameters is constructed in this study using the copula function. In addition, a dynamic reliability analysis method for slope stability is proposed using a number-theoretical method and the generalized probability density evolution method (GPDEM). First, the method is validated by comparing the results for a numerical example with those obtained by Monte Carlo simulation (MCS). Second, the traditional and proposed joint distribution models are comparatively analyzed in terms of the dynamic response and reliability. Finally, the effect of the type of copula function on the dynamic reliability of the slope is investigated. The results show that the copula theory, the number-theoretical method, and the GPDEM provide an effective approach to analyze the dynamic response and reliability of slope stability. The randomness of rockfill strength parameters is sensitive to the safety factor of the slope stability of rockfill dams. The reliability analysis method can reasonably characterize the influence of strength parameter uncertainty on dam slope stability, which makes up for the deficiency of using a single safety measurement standard in the deterministic analysis method. The copula function can reasonably characterize the nonnormal distribution characteristics of rockfill strength parameters, improve the calculation accuracy of the slope stability reliability of rockfill dams, and provide an important scientific basis for the accurate safety assessment of dam slope stability. The type of copula function has an important impact on the dynamic reliability results for slope stability. Thus, it is extremely important to build a joint distribution model of rockfill strength parameters based on a rational selection of the optimal copula function. [ABSTRACT FROM AUTHOR]

Anomalous values commonly observed in monitoring data can severely impact dam structural health monitoring. Hence, it is crucial to establish reliable models for identifying various anomalies in dam monitoring systems. This paper develops a multi-point anomaly recognition model by coupling improved Local Outlier Factor (LOF) and mutual validations considering spatio-temporal correlation. The proposed model is evaluated using real-world displacement data from concrete and rockfill dams, and the results demonstrate its satisfactory accuracy and superior robustness across the whole dam monitoring section. This work provides a dependable database for dam safety assessment and a valuable reference for recognizing the cause of anomalies. Further research directions should be focused on the recognition of anomalies in more complex monitoring data and the processing of data after removing outliers. • A framework is developed to construct two-dimensional point sets as identification samples. • The proposed multi-point model achieves improved accuracy and robustness of dam monitoring data anomaly recognition. • Analysis for spatiotemporal correlation of outliers offers a novel perspective on the anomaly cause recognition. • The identification results can provide a reliable database for further dam safety assessment. [ABSTRACT FROM AUTHOR]

The evaluation of slope stability reliability under the condition of incomplete probability information is one of the most popular issues in geotechnical engineering. The key difficulty in the issue lies in how to effectively establish a joint probability distribution model that conforms to the distribution characteristics of shear strength parameters under the condition of incomplete probability information. In this paper, based on the incomplete probability information of the nonlinear strength parameters of rockfill, the joint distribution model of the nonlinear strength parameters will be established using the Copula function. Combined with a radial basis function network (RBFN), an intelligent response surface method for reliability analysis of rockfill dam slope stability systems will be proposed. Its feasibility and validity will be demonstrated through an example. The influences of the Copula function type and sample number on the reliability of the stability system of rockfill dam slope will be systematically studied based on the constructed intelligent response surface. The results indicate that the Copula function could reasonably describe the correlated, nonnormal distribution characteristics of the nonlinear strength parameters and effectively construct their joint distribution model. The Copula function could provide reliable, statistically significant parameter samples for reliability analysis of the stability system of rockfill dam slopes. The traditional independent normal distribution ignores the correlated, nonnormal distribution characteristics of the nonlinear strength parameters of the rockfill, which result in the smaller failure probability and overestimation on the reliability of the stability system of the dam slope. The Copula function type and the number of samples have a significant impact on the reliability of the stability system of a rockfill dam slope. Therefore, it is recommended that as much test data as possible is obtained for statistical analysis, and the optimal marginal distribution function and Copula function are selected to improve the accuracy of the failure probability analysis of the rockfill dam slope stability system, which is of great engineering significance in the safety evaluation of a dam. [ABSTRACT FROM AUTHOR]

• Stochastic ground motion generation method and the DPIM is connected with the number theory point selection method. • DPIM is introduced into the field of stochastic dynamic analysis of high CFRD for the first time. • Non-stationary ground motion is generated based on the latest standard for the seismic design of hydraulic structures. • Sliding damage of the slope is more likely than the deformation damage of the dam from the perspective of probability. 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. [ABSTRACT FROM AUTHOR]

Abstract This research mainly addresses evaluating the seismic reliability and analyzing the random dynamic response of high concrete-faced rockfill dam (CFRD) slopes suffering from the near-fault earthquakes by establishing a novel method of generating the representative acceleration time histories coupled with the recently proposed generalized probability density evolution method (GPDEM). A probability evaluation is performed after generating two groups of near-fault ground motions, pulse-like and non-pulse-like earthquakes, coupling a series of statistical stochastic parameters with the spectral representation-random function method. A 242-m-high CFRD is selected as an example for finite element stochastic dynamic time series analysis, and second-order statistical values (including mean and standard deviation) and probability information of three indices the safety factor, the cumulative time of safety factor ≤ 1.0 (F s ≤ 1.0) and the maximum cumulative slippage of the dam slopes are determined, respectively. The effective non-stationary near-fault earthquakes will be adopted to determine the stochastic earthquake loading for the dynamic response evaluation of dam slopes. The statistical and probabilistic results demonstrate that the seismic characteristics make a great difference to the seismic response of slope stability as well as the pulse properties. The stochastic near-fault earthquakes combined with the GPDEM can evaluate seismic performance and reliability effectively from the perspective of randomness, and the failure probability can be obtained directly. Highlights • Seismic performance evaluation of dam slopes subjected to near-fault ground motions is investigated. • A novel method of generating the near-fault ground motions is established. • A recently developed GPDEM is coupled with the representative acceleration time histories. • Statistical and probability information are compared between non-pulse-like and pulse-like ground motions. [ABSTRACT FROM AUTHOR]

Determining the failure probabilities of high concrete-faced rockfill dams (CFRDs) is an important component of seismic performance assessment, considering the randomness of earthquake ground motions. In this paper, a new efficient methodology that couples the recently developed generalized probability density evolution method (GPDEM) with the spectral representation-random function method is proposed to evaluate the seismic performance of high CFRDs from a stochastic perspective. A set of representative acceleration time histories of non-stationary earthquake ground motions with complete probability are generated based on an evolutionary power spectral density model through an iterative correction to produce a good fit between the average response spectrum and the code spectrum in China’s hydraulic structure seismic code. Then, a series of deterministic dynamic calculations for a 200-m CFRD based on a generalized plasticity model modified for rockfills and a generalized plasticity interface model are performed to solve the GPDEM equation. A new face-slab damage index that considers double physical parameters (demand capacity ratio and cumulative overstress duration based on stress) is presented and its probability information is determined by constructing a virtual random process. Finally, probability density functions and cumulative distribution functions are obtained under two seismic levels by considering three performance indices corresponding to deformation, stability of dam slope and safety of face-slabs. The failure probability of different failure grades demonstrates that this new method has a good applicability to seismic performance assessment of high CFRDs. [ABSTRACT FROM AUTHOR]

This paper investigates the seismic reliability of earth-rockfill dam slopes under stochastic earthquake excitation considering strain-softening behaviour of rockfill materials. A new and efficient methodology that couples a recently developed generalized probability density evolution method (GPDEM) with a spectral representation-random function method is presented to assess the seismic reliability. To solve the GPDEM equation, the stochastic seismic responses analysis of a 242-m concrete face rockfill dam (CFRD) is translated into a series of deterministic dynamic calculations. The probability information and seismic reliability of the safety factor demonstrate that the results between the simulations considering unsoftening and softening behaviour of the rockfill materials become increasingly different as the earthquake intensifies, and strain-softening behaviour gradually appear under seismic excitation. Thus, considering the softening characteristic of rockfill materials, is of great significance to analyze the seismic safety of high earth rockfill dams. The traditional index for evaluating dam slope stability with safety factor is compared with a new index the cumulative time of the safety factor less than 1.0 ( F s < 1.0), suggesting that the new index is more reasonable to assess the seismic reliability of dam slopes. The results indicate that the GPDEM is an effective approach to seismic reliability assessment from the stochastic viewpoint and can directly reflect the failure probability. [ABSTRACT FROM AUTHOR]

In this paper, a seismic fragility analysis method based on incremental dynamic analysis (IDA) is extended to evaluate the seismic performance of high concrete face rockfill dams (CFRDs). Permanent deformation and face-slab damage index using a modified generalized plasticity model for rockfills and a plastic-damage model for face-slabs are considered to be dam damage measures (DMs) after defining a new face-slab damage index. The verification to damage index through the Zipingpu CFRD and previous research indicates that the grading standards are reasonable. Fragility curves and the probabilities are determined for each DM under different earthquake intensities. The results of fragility analysis demonstrate that this method can provide a strong scientific basis for predicting the earthquake destruction and loss of high CFRDs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. • The random samples are generated by stochastic ground motion model and GF-discrepancy. • GPDEM is adopted to analyze the stochastic dynamic response and probabilistic response of the CFRD. • The randomness of material parameters, seismic excitation, and their coupling in the CFRD are studied. • The performance-based seismic safety evaluation framework for CFRD is proposed based on the vulnerability analysis. [ABSTRACT FROM AUTHOR]

Because rockfill strength and seismic ground motion are dominant factors affecting the slope stability of rockfill dams, it is very important to accurately characterize the distribution of rockfill strength parameters, develop a stochastic ground motion model suitable for rockfill dam engineering, and effectively couple strength parameters and seismic ground motion to precisely evaluate the dynamic reliability of the three-dimensional (3D) slope stability of rockfill dams. In this study, a joint probability distribution model for rockfill strength based on the copula function and a stochastic ground motion model based on the improved Clough-Penzien spectral model were built; the strength parameters and the seismic ground motion were coupled using the GF-discrepancy method, a method for the analysis of dynamic reliability of the 3D slope stability of rockfill dams was proposed based on the generalized probability density evolution method (GPDEM), and the effectiveness of the proposed method was verified. Moreover, the effect of different joint distribution models on the dynamic reliability of the slope stability of rockfill dams was revealed, the effect of the copula function type on the dynamic reliability of the slope stability was analysed, and the differences in the dynamic reliability of the slope stability under parameter randomness, seismic ground motion randomness, and coupling randomness of parameters and seismic ground motion were systematically determined. The results were as follows: the traditional joint distribution models ignored related nonnormal distribution characteristics of rockfill strength parameters, which led to excessively low calculated failure probabilities and overestimations of the reliability of the slope stability; in practice, we found that the optimal copula function should be selected to build the joint probability distribution model, and seismic ground motion randomness must be addressed in addition to parameter randomness. [ABSTRACT FROM AUTHOR]

The spatial variability of rockfill properties is the key factor affecting stochastic seismic responses. Herein, an efficient probabilistic analysis method for stochastic seismic analysis named the generalized probability density evolution method (GPDEM) is proposed and combined with the random field generated by K-L decomposition to evaluate the stochastic seismic responses of concrete-faced rockfill dams (CFRDs) during earthquakes. The vertical plastic deformation is selected as a significant index to quantify the effect of rockfill spatial variability. First , a series of 2D random fields and a finite element model of the CFRD profile are established. Each realization of random fields is assigned to each grid depending on the coordinates. Then , four working conditions (different constitutive model parameters, cross-correlation coefficients, concrete-faced slab contact positions and earthquake intensities) are investigated and compared in CFRD dynamic calculations. Finally , the GPDEM-based vertical plastic deformation results are obtained, and probabilistic analyses are carried out to evaluate the influence of rockfill property uncertainty on the stochastic seismic responses. Multiple figures of the probability density function (PDF) and cumulative distribution function (CDF) of dynamic calculations are shown as examples to analyze the marked effect of rockfill spatial variability. The results demonstrate that the control parameter (M f) is the most influential parameter of stochastic seismic responses in the GPDEM. The cross-correlation coefficient increases the probability of large vertical plastic deformation compared to zero. Moreover, the nonfaced-slab side is more sensitive to the effect of rockfill uncertainties. Increasing the seismic motion intensity causes a larger probability beyond the limit. [ABSTRACT FROM AUTHOR]

• Fragility of high CFRDs considering mainshock-aftershock sequences is investigated. • All materials of the CFRD are simulated using elastoplastic models. • EDP which can best reflect cumulative damage effect of aftershocks is selected. • The effects of aftershock on the fragility of CFRDs are discussed from two aspects. Numerous earthquake disasters have demonstrated that secondary damage to structures induced by aftershocks may seriously threaten the seismic safety of structures since the mainshock may have already weakened structural integrity. This paper investigates the fragility of a 200-m high concrete face rockfill dam (CFRD) subjected to mainshock-aftershock sequences based on multiple stripes analysis (MSA). A modified generalized plasticity model and a plastic-damage model are used to describe the nonlinearity of the rockfills and the concrete face slabs, respectively. A series of nonlinear dynamic time history analyses for the CFRD under mainshock-aftershock sequences with different intensity combinations are conducted. The analysis focuses on the deformations, the shear strains and the damage index (DI) of the face slabs. According to the analysis results, the vertical deformation is the best indicator of the cumulative damage inflicted by aftershocks on the high CFRD. Then, considering the importance of face slab damage to the integrity and performance of the CFRD, the influences of aftershocks on the probability of the CFRD reaching a specific limit state are discussed based on vertical deformation and DI. The results reveal that aftershocks can significantly increase the fragility of the CFRD when it has been damaged by mainshocks. [ABSTRACT FROM AUTHOR]

Many high concrete-faced rockfill dams (CFRDs) are located in areas with high earthquake intensity where the ground motions are characterized by randomness; consequently, it is significant to study the seismic responses and evaluate the seismic performance using dynamic time-history analysis by a stochastic vibration method based on failure probability theory. In this paper, a recently developed generalized probability density evolution method (GPDEM) coupled with a spectral representation-random function method is verified to be suitable for strongly nonlinear structures in high CFRDs during earthquakes by comparing the accuracy and efficiency of the GPDEM with those of the Monte Carlo method (MCM). The GPDEM combined with the currently deterministic dam finite element time-history response analysis using a series of simple and common methods, is adopted to analyze the stochastic seismic responses, dynamic probability evaluation and failure probability of high CFRDs subjected to stochastic earthquake excitation. The statistical and probabilistic information of the typical physical quantities are compared between the GPDEM and MCM after a series of deterministic dynamic calculations, and the dynamic nonlinear behavior of rockfills and the random characteristics of ground motions are presented. The strong correspondence between the results obtained using the traditional stochastic probability MCM analysis and the GPDEM analysis demonstrates the accuracy and effectiveness of the newly proposed method despite its significantly lower computational burden. Finally, the failure probabilities of a high CFRD with different failure grades based on three universal evaluation indices are determined by constructing a virtual GPDEM process. The results demonstrate that the GPDEM shows promise as an approach that can reliably analyze strongly nonlinear structures, such as earth-rockfill dams and other geotechnical engineering structures. • Seismic time-history response of high CFRDs was analyzed using some simple models and methods. • The precision and efficiency of GPDEM were verified by comparing with MCM. • The statistical and probability information of three typical physical quantities was compared. • The failure probabilities of three universal evaluating indices were obtained based on GPDEM. • The seismic performance of high CFRDs was evaluated from stochastic and probability viewpoint. [ABSTRACT FROM AUTHOR]

This paper introduces a novel seepage parameter inversion method for earth–rockfill dams. The method utilizes pore water pressure data and employs a radial basis function (RBF) neural network as a surrogate model, which is optimized with the improved chaos sparrow search algorithm (ICSSA) using a hybrid strategy. The improved surrogate model (ICSSA–RBF) establishes a nonlinear relationship between the seepage parameter and pore water pressure. Unlike the original algorithm, the algorithm proposed in this paper can avoid three principal problems: the optimization search falling into a local optimal value, the population diversity decreasing during the iteration process, and the RBF neural network being prone to overfitting. The ICSSA, which is proficient in recognizing an objective function's significant values, is also chosen for identifying the parameters. To validate the effectiveness of the proposed approach, four classical test functions, a numerical model, and an actual engineering project are considered for the comparative analysis. The study outcomes reveal that ICSSA–RBF exhibits an exceptional level of prediction accuracy, with a mean relative error of less than 5‰. The findings also affirm the potential of the proposed approach in parameter identification and its superiority in facilitating the evaluation of seepage parameters in earth–rockfill dams. [ABSTRACT FROM AUTHOR]

Amplitude, frequency content and duration are the three main features of earthquake ground motions. The first two features have been fully considered in the seismic design of high concrete-faced rockfill dams (CFRDs). However, the role of ground motion duration on the seismic performance assessment of CFRDs remains unclear. In this paper, 40 as-recorded ground motions with a broad distribution of durations modified to match a 5% damped target spectrum are selected to investigate the influence of strong motion duration on the seismic performance of high CFRDs. A generalized plasticity model for rockfill materials, a plastic damage model for face slabs and a generalized interface plasticity model to describe the relative sliding behavior between the face slabs and rockfill are adopted for the dynamic response analysis based on a 2D 200-m-high regular CFRD. The vertical displacement, horizontal displacement, plastic shear strain and a face-slab damage index are used as the dam damage measures (DMs). The correlation coefficient R 2 is selected to reflect the degree of the relationship between strong motion duration and DMs. The results indicate that the vertical displacement, horizontal displacement, and plastic shear strain are positively correlated with strong motion duration, but the face-slab damage index has a low correlation. Therefore, the influence of strong motion duration should be considered in the seismic performance assessment of high CFRDs, and the use of short durations of strong ground motion in the design and seismic performance assessment of CFRDs may overestimate dam performance. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

With the rapid growth of economic, a growing number of earth and rockfill dams, especially high concrete faced rockfill dams (CFRDs), are being constructed in the intensity earthquake region in southwest of China. Their proximity to earthquake prone areas sets an imperative to evaluate the seismic performance of these dams. It can partially be evaluated based on fragility analysis and then fragility curves of the dams will be obtained. However, the establishment of fragility curves requires numerous numerical simulations with the finite element method (FEM). In this study, a support vector machine (SVM) is introduced to improve the computational efficiency of estimating structural response. Firstly, one hundred ground motion records are synthesized based on information given in the design scenario, and the corresponding intensity measures (IMs) can be obtained from each record. Secondly, numerical simulations are conducted by FEM and the corresponding damage measures (DMs) can be obtained. Three DMs are considered in this study, including vertical displacement, plastic shear strain, as well as the damage index (DI) of the face slab. Then, SVM models corresponding to the three DMs are trained according to the IMs and DMs, respectively. Finally, the fragility curves of different limit states based on the three DMs are calculated. This method of combining FEM and SVM is used for analyzing the seismic fragility of a 200 m CFRD. The results indicate that this method is effective for fragility analysis of CFRDs. • Fragility analysis of high CFRDs is investigated combining FEM with SVM. • Three DMs which can reflect the response of dam are selected. • Fragility curves under different limit states are calculated based on PGA. • All materials of the CFRD model are simulated by elastoplastic models. [ABSTRACT FROM AUTHOR]