In order to evaluate the applicability of the latest generation GPM IMERG satellite precipitation products in Jiangsu Province, the measured precipitation data of 73 ground stations were selected as references. Using statistical indicators and extreme precipitation index, the accuracy evaluation of GPM IMERG precipitation products were conducted from the perspectives of day, month, season, and their extreme precipitation monitoring capabilities were evaluated. The results show that the GPM satellite precipitation products have good observation effects in Jiangsu region. At the daily and monthly scales, their overall and regional data have a high correlation with ground station measured data (C_CC≥ 0.77), and the correlation becomes more significant with the increase of time scale. At the same time, the GPM satellites overestimate the measured precipitation, and the R_RMSE at the monthly scale is relatively higher. There are certain differences in the observation accuracy of GPM satellites in different seasons, and the winter observation effect is the best, with high correlation and the lowest observation error (C_CC=0.92, R_RMSE=26.37 mm, R_RB=23.4%). The GPM satellite has good ability to monitor extreme precipitation and can observe and describe the occurrence and intensity of extreme precipitation in Jiangsu region, especially in the southern Jiangsu region, with better observation effect.

In order to meet the flood discharge and irrigation requirements of tributary channels, it is of great practical significance to master the water flow diversion characteristics of the three-branch river channel. Based on numerical simulation and physical model experiments, the water level changes, velocity distribution, and flow allocation characteristics at the mouth of three tributaries river under different branching angles were studied. The results show that for a three-branch river channel, the larger the branching angle, the smaller the flow velocity in the tributary is, and the flow allocation in the variable angle side gradually decreases, while the flow allocation in the fixed angle side and the main branch gradually increases. Based on dimensional analysis, a three-branch river flow diversion ratio calculation formula was obtained considering the Froude number at each branch inlet. The formula was verified, and it was found that the prediction accuracy of the formula for the flow diversion ratio of the tributary channels in a three-branch river system was good.

The number of long-distance, high drop, pressurized, and self-flowing water pipeline projects is increasing in the northwest region. Most of the pipelines show undulating shapes, and the hydraulic transition process of the entire pipeline system becomes very complex during operation and regulation. When the water hammer protection setting is unreasonable, it will lead to pipe explosion, seriously threatening the safety of people and property. In order to ensure the safe operation of the entire system, the characteristic line method and the HAMMER V8i water hammer analysis software were used to analyze the hydraulic transition process of a long and high drop inverted siphon in a water transmission project. By setting isolation and maintenance valves, submerged energy dissipation valves, and exhaust valves along the pipeline, and setting regulating valves at the end of the pipeline, the positive pressure of the pipeline system is effectively controlled during normal operation and valve closure. By simulating the hydraulic transition process of the pipeline system under different flow rates after pipe explosion, the installation of water hammer protection equipment minimizes the harm caused by pipe explosion. The flow rate of the pipeline system after complete pipe explosion is not continuous. The action time and operation rules of the water hammer protection equipment for long-distance and high drop inverted siphon lines play a crucial role in the safety of the entire system. The research results can provide reference for the similar projects.

According to the prototype characteristic curve of the pump set, there will be a deviation between the theoretical value and the actual value when guiding the actual scheduling of the pumping station, which will affect the accuracy of daily scheduling and energy consumption evaluation. Therefore, taking Liyuzhou pumping station as an example, this paper proposes a method combining the measured data of the pumping station and the law of similarity to correct the prototype characteristic curve of the pump set. The flow optimization distribution model is established in terms of the actual operating conditions, and the difference of optimal flow distribution scheme of pumping station between the characteristic curve of the pump set before and after the correction is analyzed. The results show that the deviation between the actual operating head and the theoretical head is mainly concentrated in 8%-11%, and the deviation between the actual operating efficiency and the theoretical efficiency is mainly concentrated in 6%-9% when the prototype characteristic curve of the pump set is used. When the flow optimization distribution scheme is selected through the corrected characteristic curve of the pump set, the results are more in line with the actual operation situation, which can effectively strengthen the guiding role of the flow optimization distribution scheme of the pumping station on the actual scheduling.

Addressing the issues of single model algorithm, low accuracy, and poor generalization in existing shield tunneling speed prediction methods, this study proposes a shield tunneling speed prediction approach to improve prediction accuracy based on Variational Mode Decomposition (VMD), Dung Beetle Optimizer (DBO), and Stacking ensemble learning. Firstly, to obtain more effective data, VMD is applied to decompose and reconstruct the original data to obtain denoised construction parameter data for subsequent model prediction. Secondly, based on the ensemble learning strategy, Support Vector Regression (SVR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) models are selected as base learners, while Gaussian Process Regression (GPR) is chosen as the meta-learner to construct a Stacking ensemble learning prediction model with higher prediction accuracy and stronger generalization ability. Thirdly, to further enhance prediction accuracy, DBO is employed to optimize the hyperparameters of the ensemble learning model. Finally, this prediction method is applied to the shield tunneling construction of a water diversion tunnel project in Henan Province and compared with other prediction methods. Compared to other single models (SVR, RF, XGBoost), the results indicate that the proposed method achieves higher prediction accuracy, with average accuracy improvements of 7.76%, 6.70%, and 4.97%, respectively, providing a new approach for shield tunneling speed prediction.

Perforated structures are commonly found in engineering applications, where stress concentration around holes significantly affects structural load-bearing capacity and safety. Therefore, accurate mechanical analysis of perforated structures is essential. However, the traditional finite element analysis methods face several challenges, including complex mesh generation, high computational resource requirements, and poor convergence when dealing with perforated structures. To overcome these challenges, a finite element analysis method based on the superposition principle is proposed. This approach replaces the original model with a simplified equivalent model featuring a less complex mesh for simulation. The stress field of sub-models is subsequently employed to correct the stress distribution around holes in the equivalent model. Comparative results indicate that the discrepancy between the equivalent model and the original model is within 5%. The equivalent model achieves a 25.2% reduction in mesh elements and a 75.1% reduction in simulation time, substantially improving simulation efficiency.

To accurately calculate the effective range of vibration rods in reinforced concrete, this study proposes a new prediction model for the effective radius of vibration rods based on the rheological theory of fresh concrete. Under the assumptions that the vibrated concrete exhibits pseudoplastic fluid characteristics and the flow in the steel mesh is equivalent to seepage through porous media, an expression for the effective radius of the vibration rod in reinforced concrete is derived. The empirical parameters in the expression are then empirically fitted in conjunction with experimental results. By comparing the model calculations with experimental values, it shows that, except for a few cases with low vibration intensity of the rod, the overall prediction accuracy of the effective radius prediction model is higher. Considering that the vibration intensity of the rods used in concrete pouring at construction sites is generally high, the model can effectively guide on-site compaction operations and quantitatively evaluate the impact of steel bar layout schemes on the vibration range of the rod.

To ensure the timeliness of frost resistance testing of hydraulic concrete and improve the safety of construction and operation of project, the methods for testing the frost resistance of concrete were systematically reviewed. The standard differences among slow freezing method, fast freezing method, single-sided freeze-thaw method and salt-resistant erosion method were compared. Two new trends were analyzed including the rapid detection technology of frost resistance based on the rapid freezing method and the rapid detection technology of concrete relying on process parameter control. The new ideas for rapid testing methods of frost resistance were proposed based on structures parameters of hardened concrete, accelerated destructive experiment, key process parameters of freezing and thawing. The concept of dedicated curves was established, and the specific procedures of the new methods was clarified. The work of all the above could provide new ideas for the frost resistance testing of hydraulic concrete.

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.

Based on the hourly precipitation data (1980-2019) from 142 national stations in Hebei Province, Mann-Kendall (MK) trend and mutation test, K-means clustering, and hydrometeorologically homogeneous region methods were used to systematically analyze the temporal evolution characteristics and spatial distribution patterns of short-term extreme precipitation in Hebei Province. The results show that significant regional differences exist in interannual variation of short-term extreme precipitation, with an upward trend in high-altitude mountains and a downward trend in low-altitude plains/hills, marked by a 1996 change-point. Topography significantly influences patterns: the spatial extent decreases in plains and southern slopes but expands on northern slopes for 1 h and 3 h durations, indicating a shift towards mountainous areas. Seasonal differences are pronounced: winter/spring increases, while summer and autumn decreases significantly, with third-quarter Rx24h declining at 0.337 mm/a. The research results reveal the spatio-temporal differentiation law of short-term extreme precipitation in Hebei Province, providing a scientific basis for regional flood control and disaster reduction as well as adaptive management to climate change.