In view of the lack of research on the creep characteristics of hydraulic concrete in water from mesoscale scale, a meso-finite element model of concrete specimen of "aggregate-mortar-transition layer" was established. Based on the test data of tensile and compressive creep in water, the method of "orthogonal design-neural network-meso-finite element calculation" was adopted to implement the inversion analysis of the tensile and compressive specific creep of hydraulic concrete specimens at mesoscale. Finally, the relationship between tensile and compressive specific creep of hydraulic concrete and mortar was compared. The results show that the variation law of tension creep degree of hydraulic concrete in water is similar to that in sealed. The creep degree of mortar water is 2.4 times of hydraulic concrete water under conditions of tensile and compressive creep.

In order to address the limitations of the existing vibration trend prediction model for hydroelectric units, a vibration trend prediction method for hydroelectric units based on optimal variational mode decomposition (OVMD), time-varying filter empirical mode decomposition (TVFEMD), hunter-prey optimization algorithm (HPO), and extreme learning machine (ELM) is proposed. This method first applies OVMD to adaptively decompose the original vibration signal of the hydroelectric unit, and then further employs TVFEMD to perform a secondary decomposition of the residuals obtained from the first decomposition. Subsequently, vibration trend prediction models HPO-ELM are established for each subsequence. The final predicted vibration signal is obtained by aggregating and reconstructing the prediction results of all the sub-sequences. The research results demonstrate that this method outperforms traditional methods in terms of prediction accuracy for the vibration trend of hydroelectric units, and it has good engineering application value.

After the Deneng Xiangjiang Hydropower Station replaced the 4-blade runner with a 5-blade runner, the unit started experiencing severe vibrations, which eventually led to coupling vibrations in the powerhouse structure and posed significant safety hazards. This paper explores the vibration source and employs Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) methods for analysis. Finally, modal verification through actual measurements validates the relevant conclusions. The study reveals that the resonance is caused by the multiple frequency relationship between the runner blade rotational frequency and the natural frequencies of the powerhouse structure. The research on the vibration issue at this power station hold great practical value.

The problem of standard disconnection often exists in the two-level drainage mode of plain river network cities in China. As a result, when heavy rainfall occurs, the hydraulic characteristics and drainage capacity of pipe network system are affected by both rainfall intensity and water level of drainage water, making it difficult for waterlogging to discharge out. Therefore, taking the municipal drainage system and water drainage system of Suzhou Industrial Park as an example, the multi-scenario flood process simulation based on SWMM was carried out, and the analysis showed that when the river water level was between 1.70 m and 2.30 m, the main reason for the water accumulation in the study area was the insufficient capacity of the current pipe network system itself, and the river water level aggravated the water accumulation. When the water level exceeded 2.30 m and keep rising, the drainage capacity of the pipe network system decreased sharply, and the river level gradually became the main factor restricting the flow capacity of the pipeline and aggravating the degree of water accumulation. It is suggested that the maximum water level for river drainage control in the study area should be around 2.30-2.32 m. This conclusion can provide reference for urban river level regulation to improve urban drainage and waterlogging capacity.

River bank collapse is very common in natural rivers and plays an important role in the evolution of river channels. In order to quantitatively study the influence of river bank soil properties and bank slope inclination on river bank stability, the BSTEM model for calculating river bank stability and bank toe erosion was adopted, and six typical river bank materials were selected to study the stability of homogeneous river banks under six bank slope inclination angles. Under the condition of ignoring the water table, the collapse modes of non-cohesive bank slope and cohesive bank slope are different. For non-cohesive bank, the dominant factor affecting bank stability is the effective internal friction angle. The larger the effective internal friction angle is, the more stable the bank is. For cohesive bank, the dominant factor affecting the stability of the cohesive bank is effective cohesion. The greater the effective cohesion is, the more stable the bank is. When the effective cohesion difference is the same, the smaller the absolute value of the effective internal friction angle difference is, the more the safety factor increases. The increase of bank slope inclination reduces river bank stability and the safety factor. The larger the effective internal friction angle of the non-cohesive bank is, the more sensitive the safety factor to the change of bank slope inclination is. For cohesive banks, the greater the effective cohesion is, the more sensitive the safety factor to the change of bank slope inclination is.

Conductivity is an important parameter to measure water quality. High-frequency monitoring of water conductivity plays an important role in water quality management. Due to the complexity of field conditions, equipment failure often leads to data loss. In order to improve the high-frequency monitoring data, machine learning model was used to predict the conductivity content in water body based on the meteorological and physical indexes obtained from high-frequency monitoring. The results show that the random forest regression model has the best prediction effect, with its determination coefficient R² reaching 0.996, root mean square error (R_RMSE) 1.31 μS/cm, and mean relative error (M MRE) 0.38%. The pH value contributed the most and was the dominant factor affecting the conductivity. The results are conducive to optimizing the field high-frequency monitoring system platform, improving the high-frequency monitoring data, which provides scientific basis for water quality management.

In view of the complex and changeable construction site and high difficulty in construction of water conservancy safety, the risk assessment of all hazard sources is the premise of safety control of a project. The traditional LEC method has the defects of large influence of subjective factors and unclear weight of each hazard source. Based on the introduction of expert credibility, the background differences between risk evaluation subjects were converted to quantitative analysis, and the subjective impairments was modified. This paper combined fuzzy comprehensive evaluation method with traditional LEC method to establish the risk evaluation index system. By calculating every index weight factor with the modified risk values in LEC method, the risk assessment was converted from qualitative to quantitative by membership degree matrix and the defection of imprecise weight factor in LEC method was solved. Finally, a verification of Xinmeng River shows that the objectivity of risk assessment of hazard sources has been improved significantly through the modified method, which provides scientific basis for the risk hierarchical control of water conservancy safety.

Dry-wet cycle effect is an important factor affecting slope stability in red mudstone reservoir area. Triaxial consolidation undrained shear experiments, CT scans and high precision scanning electron microscopy experiments were carried out to investigate the mechanical and fracture evolution characteristics of in situ weathered mudstones during dry and wet cycles. The results show that the stress-strain relationship of red-bed mudstone presents strain softening characteristics at low confining pressures and strain hardening characteristics at high confining pressures. The shear strength parameters of red-bed mudstone decrease gradually during the dry-wet cycle. The volume content of cracks decreases exponentially with the increase of the time of dry-wet cycles, and has a negative linear correlation with cohesion function. The microstructure of mudstone gradually breaks down in the process of dry-wet cycles, leading to the connectivity of cracks and the attenuation of mechanical properties.

Rainfall will affect the characteristics of slope flow field. Due to the continuous flow of fluid, the surface runoff and slope seepage usually exist a coupling linkage phenomenon. The surface runoff is described by the N-S equation, while the Darcy’s law is used to describe the seepage in the slope. The analytical solutions of velocity distribution, pressure and discharge as well as the semi-analytical solution of runoff surface line are derived by the separation of variables method under the velocity slipping boundary condition at the interface between runoff and soil. In addition, the explicit Runge-Kutta method is adopted to solve the water depth, velocity and discharge values at different locations. The results show that the steeper the slope is, the faster the fluid movement and the shallower the water depth is. The greater the rainfall intensity is, the deeper the overall water depth is. The flow velocity at the slope surface is not equal to 0. The closer to the downstream, the larger the proportion of runoff flow discharge is. The study can provide reference for the research of the slope flow field characteristics.

The load rejection process is one of the most dangerous transients in pumped storage hydropower plants. The current design criteria of plant guarantee that the lowest pressure in draft-tube inlet is higher than the saturation pressure during transients, but there is still local cavitation inside the pump-turbines. The one-dimensional pipeline and three-dimensional pump-turbine coupled computational fluid dynamics simulation method was used to simulate the simultaneous load rejection process in a pumped-storage hydropower plant. The results show that a spiral cavitation cavity is in the center of the draft-tube inlet, and five wedge-shaped cavitation cavities are in the outlets of runner channels. The collapse of the spiral cavitation cavity in the draft-tube leads to instantaneous pulse impacts on the pressure and runner forces. There is no obvious impact when the wedge cavities collapse.