Water conservancy projects have the functions of flood control, power generation, water supply, and irrigation, and play a vital role in the survival and development of human society

As an essential load of the concrete dam, the abnormal change of uplift pressure directly threatens the safety and stability of the concrete dam. Therefore, it is of great significance to accurately and efficiently excavate the hidden information of the uplift pressure monitoring data to clarify the safety state of the concrete dam. Therefore, in this paper, density-based spatial clustering of applications with noise (DBSCAN) method is used to intelligently identify the abnormal occurrence point and abnormal stable stage in the monitoring data. Then, an application method of measured uplift pressure is put forward to accurately reflect the spatial distribution and abnormal position of uplift pressure in the dam foundation. It is easy to calculate and connect with the finite element method through self-written software. Finally, the measured uplift pressure is applied to the finite element model of the concrete dam. By comparing the structural behavior of the concrete dam under the design and measured uplift pressure, the influence of abnormal uplift pressure on the safety state of the concrete dam is clarified, which can guide the project operation. Taking a 98.5 m concrete arch dam in western China as an example, the above analysis ideas and calculation methods have been verified. The abnormal identification method and uplift pressure applying method can provide ideas and tools for the structural diagnosis of a concrete dam.

The system identification of concrete dams using seismic monitoring data can reveal the practical dynamic properties of structures during earthquakes and provide valuable information for the analysis of structural seismic response, finite element model calibration, and the assessment of postearthquake structural damage. In this investigation, seismic monitoring data of the Pacoima arch dam were used to identify the structural modal parameters. The identified modal parameters of the Pacoima arch dam, derived in different previous studies that used forced vibration tests (FVT), numerical calculation, and seismic monitoring, were compared. Meanwhile, different modal identification results using the input-output (IO) methods and the output-only (OO) identification methods as well as the linear time-varying (LTV) modal identification method were adopted to compare the modal identification results. Taking into account the different excitation, seismic input, and modal identification methods, the reasons for the differences among these identification results were analyzed, and some existing problems in the current modal identification of concrete dams are pointed out. These analysis results provide valuable guidance regarding the selection of appropriate identification methods and the evaluation of the system identification results for practical engineering applications.

To improve the efficiency, accuracy and adaptivity of the parameter inversion analysis method of a rockfill dam, this study aims to establish an adaptive model based on a harmony search algorithm (HS) and a mixed multi-output relevance vector machine (MMRVM). By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. Therefore, the finite element method with time consumption can be replaced by the MMRVM. Because of its excellent global search capability, the HS is used to optimize the kernel parameters of the MMRVM and the material parameters of a rockfill dam. Because the parameters of the HS and the variation range of the MMRVM parameters are relatively fixed, the HS-MMRVM can imbue the inversion analysis with adaptivity; the number of observation points required and the robustness of the HS-MMRVM are analyzed. An application example involving a concrete-faced rockfill dam shows that the HS-MMRVM exhibits high accuracy and high speed in the parameter inversion analysis of static and creep constitutive models. The applicability of the HS-MMRVM in hydraulic engineering is proved in this paper, which should further validate in inversion problems of other fields. An adaptive inversion analysis model is established to avoid the parameters of traditional methods that need to be set by humans, which strongly affect the inversion analysis results. By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. To reduce the data dimensions and verify the model’s robustness, the number of observation points required for inversion analysis and the acceptable degree of noise are determined. The confidence interval is built to monitor dam settlement and provide the foundation for dam monitoring and reservoir operation management.

The deformation properties of concrete arch dams are affected by the synergistic effects of multiple factors, featuring strong, multidimensional spatialtemporal evolution and distribution characteristics. This paper proposes a zoned safety monitoring model for arch dam deformation based on spatialtemporal similarity and model optimization to evaluate the deformation safety state of arch dam structures. First, zoned clustering of the deformation monitoring points at different locations of an arch dam was performed using a panel data multi-index clustering method to determine the deformation laws at different positions of the dam. Next, multipoint comprehensive displacements of the deformation properties of each zone were extracted using principal component analysis to extract the uniform deformation law of the monitoring point in each zone. Finally, we adopted Bayesian model selection (BMS) and Bayesian model averaging (BMA) for the regression model set, considering the uncertainty of the model. The engineering case study showed that BMA yielded robust and effective prediction results for the deformation of the arch dam. The analysis of the zoned deformation mechanism indicated that the deformation of the arch dam followed the general rule. The temperature component of the arch dam was mainly reflected in the middle with a hysteresis effect, and the time-dependent component was evident in both sides of the dam shoulder. The arch dam deformation safety monitoring model proposed in this study has strong robustness and interpretability, which can provide valuable technical support for analyzing the evolution of arch dam deformation properties.

As a high-efficiency and low-investment method of dam construction, blast-fill dams have been widely used in water conservancy, mining engineering, soil and water conservation, disaster prevention and other projects. Through collecting data on the main projects of the blast-fill dams, the characteristics and development trends of blast-fill dams are analyzed in detail. Meanwhile, the design requirements of impervious bodies in the initial and reinforcement stages are systematically reviewed. Subsequently, with measured data of a typical blast-fill dam, the structural characteristics of blast-fill dams after blasting and the validity of the phreatic line height after reinforcement are analyzed using the discrete element method. We conclude that an appropriate construction schedule and flexible impervious material are critical features of the impervious body for a dam with large deformation. When the dam deformation is stable, a secondary treatment should be considered for the impervious body to improve the dam safety. The design ideas for the impervious body of blast-fill dams are also applicable to other dam types with large deformation for risk reduction, such as high rockfill dams, soft-rock dams and tailings dams, and have a certain significance for reference in the treatment of landslides and confined lakes.