The long-term prediction of concrete dam deformation is an important requirement for maintaining its structural integrity during actual operation. To improve the accuracy of long-term deformation prediction of concrete, a long-term dam deformation prediction model based on multi-layer perceptron (MLP) and ecoder-decoder (Ecoder-Decoder) architecture, MLP-Ecoder-Decoder (MED), was constructed. This model captured the long-term dependence of dam deformation and environmental loads through a deep auto-correlation (Deep-Auto-Correlation) mechanism, and used time series decomposition and deep auto-correlation mechanism for multi-step deformation prediction. The model was used to predict the deformation of a 250 m height arch dam in Qinghai Province under complex environmental conditions. The results show that the MED model effectively improves the prediction accuracy and has a strong advantage in extracting long-term time features.

There are problems of non-convergence and easy false alarm when formulating dam deformation monitoring indicators (which belong to fixed limits) based on the conventional low-probability method. A calculation method for formulating deformation monitoring indicators based on the low-probability method of separating aging components is proposed. Firstly, the statistical model of dam deformation is established to separate the time-dependent component. Then, aiming at the time series deformation of deducting the aging component, the annual extreme value is selected as the subsample. The corresponding deformation of the annual most unfavorable reservoir water level and temperature is selected as the subsample. The corresponding deformation of the unfavorable water level and temperature based on the combination of orthogonal test method is selected as the subsample. Then the statistical test is carried out, and the small probability method is used to formulate the deformation allowable value of deducting the aging component. Finally, the aging component is superimposed to obtain the non-convergence deformation monitoring index of the dam. Combined with the measured data of a deformation non-convergence gravity dam in southwest China, the analysis shows that compared with the monitoring index proposed by the conventional small probability method, the method based on the separation time component fully considers the time effect and enhances the reliability of the monitoring index.

Constructing a high-precision dam settlement prediction model is of great significance for ensuring the safety and risk control of dam during the construction period. Taking dam height, rainfall and aging as the influencing factors of dam settlement deformation during construction period, the long-term and short-term memory neural network LSTM algorithm is introduced, and the attention mechanism is embedded. Thus, a prediction model suitable for dam settlement of concrete face rockfill dam during construction period is proposed. The engineering application shows that the attention-LSTM model makes up for the defect that the LSTM cannot dynamically adjust the weight coefficient at the network layer, improves the computational efficiency and accuracy of the model, and has better nonlinear data processing ability, which can more accurately reflect the change trend of monitoring data in the time dimension during the construction period. The relevant experience can be used as a reference for similar projects.

Aiming at the complex karst environment of the lower reservoir of a pumped storage power station, a three-dimensional finite element model for seepage analysis was established to simulate the main buildings and karst passageways in the reservoir area. "The depth of seepage control curtain at the base of the dam is 0.5 times of the pre-dam head, the depth of seepage control curtain on both sides of the dam is 3 m below the 3 Lu line, the length of seepage control curtain on the right side of the dam is 200 m, and a single-row curtain is set up" is used as the preliminary seepage control scheme. The seepage field, infiltration slope and infiltration volume of the reservoir area were calculated. The preliminary seepage control scheme met the specification requirements. But the seepage rate and infiltration slope were close to the critical value. The four indexes of curtain depth on both sides of the bank, curtain depth at the base of the dam, length of curtain on the right bank, and double-row curtain were changed to optimize seepage control scheme. The impact of the changes of the indexes on the infiltration volume of the reservoir area was investigated so that the optimization of the seepage control scheme was put forward. The analysis results show that on the basis of the preliminary scheme, the double-row curtain is set up at the dam base, the infiltration flow at the dam base is reduced by 267.3 m³/d, and the effect of seepage control in the reservoir area is remarkable.

The pumped storage power station has the characteristics of frequent unit start-up and shutdown and working condition switching, which has great influence on the safe operation of the power station. At present, the on-site monitoring data of the vibration response of the underground powerhouse structure of pumped storage power station under the vibration load of the unit are few, especially the vibration monitoring of the unit under the transient conditions such as unit start-up and shutdown and load rejection. This paper takes the underground powerhouse of a pumped storage power station as the research object, and carries out the dynamic characteristics monitoring analysis under the transient conditions of power generation, pumping switch and different output load rejection. The results show that the peak vibration response of each typical part of the powerhouse structure under transient condition is obviously greater than that under steady condition, and the vibration response under power generation on and off condition is greater than that under pump pumping condition, but the vibration displacement and acceleration can basically meet the recommended limits of the current vibration standard. Under 100% load rejection conditions, the vibration response of the powerhouse structure is the strongest, and the maximum vibration acceleration can reach more than 30 m/s², which is easy to cause impact damage to the powerhouse structure. It is recommended to avoid 100% load rejection conditions during daily operation and maintenance of the power station. In case of occurrence, it is necessary to timely detect the key structural parts of the powerhouse to eliminate safety risks.

In order to explore the influence of pressure pulsation of the pumping unit on the powerhouse structure, the powerhouse of Dayuzhang pumping station was taken for an example. Based on the prototype observation data, the vibration source composition and vibration characteristics of powerhouse structure were analyzed using three-dimensional finite element simulation. The safety of the structure was analyzed and evaluated from the perspective of structural resonance check and vibration response. The results show that the hydraulic pulsation caused by RSI and the rotational frequency excitation caused by the operation of the unit have the greatest impact on the vibration of powerhouse under the stable operation condition of the unit, and the natural frequency of the local floor structure has a small degree of coincidence, which is easy to resonate. However, from the perspective of vibration response, the vibration response of each local part is within the allowable range, the outlet elbow and pump seat are the largest, and the pump floor slab is the smallest. This study has important theoretical value and practical significance for realizing the long-term and safe operation of the pumping station powerhouse structure.

The maximum water head endured by the floor of the high-pressure branch pipe at the Zhongdong Pumped Storage Power Station in Huizhou, Guangdong, is approximately 800 m during operation. The stability of the surrounding rock under this high internal water pressure is critical to the station's safe operation. To address this, in-situ stress and high-pressure water injection tests were conducted. Combined with three-dimensional in-situ stress field inversion, the stress field distribution, permeability characteristics, and hydraulic fracturing resistance of the high-pressure branch pipe area were analyzed, and the layout of bifurcated pipe was optimized. The results indicate that the maximum principal stress in the high-pressure branch pipe section ranges from 15.0 to 16.6 MPa, and the minimum principal stress ranges from 8.4 to 9.7 MPa. The rock permeability ranges from 0.01 to 0.19 Lu, indicating very low to low permeability. The initial high-pressure branch pipe location meets the stability requirements against uplift and seepage. However, within a 7 m range of the branch pipe opening, the class Ⅲ rock mass segment is affected by faults and does not meet the engineering requirements for hydraulic fracturing resistance. Based on a comprehensive analysis of the surrounding rock conditions, uplift resistance, hydraulic fracturing resistance, and seepage resistance, the initial high-pressure branch pipe location was shifted 10 m toward the powerhouse, which meets the stability requirements for uplift, hydraulic fracturing resistance, and seepage resistance.

The pumped storage power stations are critical infrastructure for achieving carbon neutrality goals. Based on the three-dimensional computational fluid dynamics method, the head loss characteristics in the combined diversion shaft-surge chamber arrangement are investigated. Firstly, the three-dimensional model from the upstream inlet to the inlet of the unit is established. Then, the hydraulic characteristics under different arrangement types are analyzed. Finally, the influence of the diameter of the turning section and the impedance holes on the head loss is explored under the combination arrangement. The results indicate that the pressure distributions are similar in combined and uncombined arrangements. The hydrodynamic characteristics are not deteriorated and reflective water hammer is more effective in combined arrangements. Under the combined arrangement, the larger the diameter of the turning section and the impedance hole, the smaller the head loss coefficient is. This study can provide theoretical references for the design of new structures for pumped storage power stations.

In order to solve the problem that the response ability of a large mixed-flow hydropower unit is affected by the change of operating water head, a method based on the adaptive feedforward function is proposed for the application of the turbine's primary frequency regulation function. The 3D curve function library of turbine's water head, guide vane opening and power is introduced into the primary frequency regulation feedforward control of the turbine. According to the real-time water head and power and the position of guide vane, the power change corresponding to the frequency change is calculated through the 3D database to directly affect the output of the controller. Compared with the conventional control mode of primary frequency regulation, it is verified by field practice. The experimental results show that the feedforward function can not only satisfy the consistency of the next frequency regulation performance of different water heads, but also effectively avoid setting and switching multi-group PID control parameters. Thus, it provides a new way to realize the function of primary frequency regulation of hydraulic turbine units.

To improve the efficiency and accuracy of fault diagnosis for hydroelectric units, combination of multifractal detrended fluctuation analysis algorithm and probabilistic neural network was used to establish a vibration signal feature extraction and recognition model. The binary gravity search algorithm was used to optimize its parameters. The results show that the classification accuracy of the feature extraction and recognition classification model can be improved to 99% and reduce the signal processing time to about 1.3 seconds after optimizing by the binary gravity search algorithm. The proposed vibration signal feature extraction and recognition model for hydroelectric units can significantly distinguish between the normal working state and the fault working state of hydroelectric units, achieving the purpose of using vibration signal features to diagnose faults in hydroelectric units.