Search

• Seepage failure probability of high core rockfill dams during RDD is investigated. • The randomness of the parameters is estimated by Bayesian inference. • Seepage failure is most likely to occur in the mid-term of RDD. Rapid drawdown (RDD) is an abnormal reservoir flood control operation that may cause seepage failure of high core rockfill dams. In this paper, a novel framework combining Bayesian inference and transient unsaturated seepage simulation is proposed to evaluate the seepage failure probability of the core during RDD. The dynamic hydraulic boundaries utilized in the simulation are first determined by the performance of water release structures. The extreme learning machine (ELM) is then employed as the surrogate model to establish the mapping relationship between material parameters with simulated seepage pressure and hydraulic gradient. The Bayesian inference method is applied to characterize the uncertainty of material parameters based on seepage monitoring data. Finally, the posterior distribution samples of random parameters are utilized to calculate the seepage failure probability of the core. The seepage safety of the core under different drawdown rates is studied with a real 186 m high core rockfill dam. The results reveal that a faster RDD rate can lead to an increased probability of seepage failure. The maximum failure probability is 35.56 % for the four release structures working together (about 0.316 m/h), higher than 23.16 % for the three release structures (about 0.165 m/h). It is also found that the peak of seepage failure probability often occurs in the middle stage of RDD. Therefore, to ensure the safety of the project, it is important to control the RDD rate and carefully monitor the seepage pressure. From the point of view of seepage failure, the proposed method for evaluating the safety of core rockfill dams under RDD is of high guiding significance to the risk assessment of similar projects under extreme conditions. [ABSTRACT FROM AUTHOR]

For modern high earth dams, sufficient safety margin is considered in the designs of flood discharge capacity and dam crest elevation to prevent flood overtopping. However, for high earth dams which may induce catastrophic consequences, during their long operational period, extremely hazardous scenarios which could occur and threaten dam safety need to be considered. For the earth dams located in areas with intensive seismicity, there is a possible scenario that the release structures fail due to seismic landslides and gate failures caused by a severe earthquake when the flood begins to enter the reservoir. Thus, it is desirable to investigate the influence of failure duration of release structures on dam overtopping risk. Based on the Bayesian network, a methodology for overtopping risk analysis of earth dams considering effects of failure duration of release structures is proposed. The overtopping risk of the PBG earth-rockfill dam was analyzed to illustrate the methodology. The critical release structures which dominate the dam overtopping risk are identified. The dam overtopping risk is most sensitive to the failure duration of the spillway. The tolerable failure duration of the spillway is approximately 3 days, and when the failure duration of the spillway reaches 4 days, the dam overtopping risk drastically rises to an unacceptable level. The case study suggests that the proposed methodology could be helpful to analyze the influences of possible failure durations of release structures on dam overtopping risk and could facilitate preparation for emergency plans. [ABSTRACT FROM AUTHOR]

During the application of semi-theoretical models to predict peak discharges for breached embankment dams, it is often encountered to be lack of necessary model parameters such as breach height. In order to solve this deficiency and improve the application of the semi-theoretical models for estimating the peak discharge, a mathematical relation is proposed to predict the breach height (Hb) using the water depth above breach bottom (Hw) based on a subset of a composite database (72 historical dam failures). The breach height relation has a high coefficient of determination (R2) when it is applied in the composite database. Using the prediction by the breach height relation as a substitute for the observation, these semi-theoretical models used here produce similar results in terms of both prediction accuracy and uncertainty. Moreover, the dispersion of the flood peak discharge predicted by forecasting models is weakened and the skewness is improved by adopting the breach height relation. Therefore, the application of semi-theoretical models to predict peak discharges can be improved obviously. So, it is found that the breach height using the proposed relation can be a satisfactory substitute when the observed value of Hb is unavailable in a dam failure. Besides, the prediction accuracy will decrease slightly with the increase of database, but the decrease is limited. It should be noted that the proposed breach height relation is only suitable for predicting the height of embankment dam breach in principle. [ABSTRACT FROM AUTHOR]

The health monitoring and operation behavior assessment of earth dams are research focuses in geotechnical engineering. Due to the limited monitoring data and the uncertainty of material properties, existing monitoring data-based interpolation methods and mechanism-based finite element method (FEM) can not accurately estimate the dam deformation field. Therefore, studying an accurate estimation method of the deformation field is important to guarantee the serviceability of earth dams. In this paper, a FEM-Bayesian kriging (FBK) method is proposed, in which the FEM is introduced into the Bayesian kriging framework as the source of soft data, taking the FEM results as a trend surface of the deformation field, the spatial distribution of the random residual is determined by the exact monitoring data, thereby the FEM results are corrected. In this method, data-rich but low-precision FEM results and limited but high-precision monitoring data are coupled to approach the real deformation field. A numerical experiment is designed to verify the accuracy of the proposed method, and the estimation error of the FBK is reduced by about 80% compared with traditional methods. The case study of an actual earth dam also shows that the proposed method can effectively characterize the deformation behavior of earth dams. [ABSTRACT FROM AUTHOR]

The allowable safety factors of slope stability for rockfill dams in Chinese design codes are defined irrespective of dam heights and are mainly based on the engineering experiences with respect to the rockfill dams which are lower than 200 m. It is well known that safety margins for different structures are not comparable when safety factors are taken as the measure of safety margin. Thus whether the current allowable safety factors are applicable to the rockfill dams with heights of over 200 m has been controversial in the engineering and academic field. Reliability is well known as a unified measure of safety margin for different structures. Therefore, the slope safety margins of rockfill dams with different heights can be compared in terms of slope reliability indices derived from probabilistic methods. Based on the statistical analysis of nonlinear shear strength parameters of rockfills from 14 Chinese dams, the slope reliabilities of fictitious rockfill dams of different heights designed with equal allowable safety factor are calculated and compared in this paper. It is shown that the slope failure risk of higher dams is larger than that of lower dams if the dams are designed with equal allowable safety factor rather than equal reliability. Therefore, from the perspective of maintaining consistent slope reliability levels among rockfill dams with different heights, the allowable safety factors should be prescribed in terms of dam height, i.e. the allowable safety factor for higher dams should be larger than that for lower dams. • Slope stability analysis of high rockfill dams using fixed allowable safety factor may induce misleading assessment. • Safety margins for rockfill dams designed with fixed allowable safety factor are not identical in terms of reliability. • The allowable safety factors should be prescribed in terms of dam height. [ABSTRACT FROM AUTHOR]

• An method of multi-source data-driven unsaturated seepage parameter inversion. • NSGA-II is used to generate the pareto-optimal solutions of parameters. • Parameter decision based on a comprehensive index composed of multi-source data. • Inversion results are more in line with engineering practice and have higher accuracy. The inverse parameter's estimation of unsaturated seepage models is important to ensure the safety of earth dams, while most existing studies determine the hydraulic characteristics only based on seepage pressure monitoring data, which may lead to inversion results deviating from the intrinsic properties of dam materials. This study proposed an advanced methodology for unsaturated seepage parameter inversion of earth dams driven by multi-source data. The transient unsaturated seepage behavior of earth dams is simulated using the Van Genuchten (VG) model, and the extreme learning machine (ELM) is adopted as the surrogate model to estimate the approximate simulation results. Then the multi-objective function for parameter inversion is constructed by combining the observed transient pressure data and ELM models, and the Pareto-optimal solutions are generated using the elitist non-dominated sorting genetic algorithm (NSGA-II). Multi-source information, including parameter design values, in-situ testing results, and monitoring data, are fused to construct a comprehensive index to drive the parameter decision. The proposed method is applied to the PB core rockfill dam, which has a well-established seepage pressure monitoring system. In addition, the design values and in-situ testing results of the hydraulic conductivity of the dam material are also available. The results showed that the inversion parameters of the proposed method are closer to the physical characteristics of materials and have advantages in prediction accuracy. [ABSTRACT FROM AUTHOR]