To deal with the problems such as grouting pipe blocking and uneven diffusion of grout-enriched roller compacted concrete, the rheology, fluidity, stability, strength and time-varying properties of slurry containing micro-silica powder were studied. The entropy weight ideal point method was used to determine the optimal mix proportion by considering the working characteristics of the slurry and economic cost. The results show that adding micro-silica powder can reduce the bleeding rate and improve the compressive strength. When W/B=0.4, micro-silica powder reduces the yield stress and fluidity, and increases the plastic viscosity. When W/B =0.5-0.7, the yield stress and plastic viscosity increase with the addition of micro-silica powder. The rheology of slurry is related to the thickness of water film. With the increase of water-binder ratio, the effect of micro-silica powder on slurry’s performance gradually weakens. The yield stress increases linearly with time, and the plastic viscosity increases exponentially with time. Based on entropy weight ideal point method, the optimal mixture ratio of different schemes with fixed water-binder ratio can be obtained.

In light of the difficulty of traditional single runoff prediction models to describe future variation in runoff, a monthly runoff prediction model named AVMD-GPR-CK based on adaptive variational modal decomposition (AVMD) and Gaussian process regression (GPR-CK) with physically composite kernel was proposed. In the proposed model, the runoff series was decomposed into several subseries using AVMD. Then subseries were separately modeled according to their own characteristics, and the final prediction result was the superposition of the subsequence prediction results. The AVMD-GPR-CK was applied to forecast the future 1-12 months runoff at Xiangjiaba station in the Jinsha River basin. The results show that the deterministic coefficient of the AVMD-GPR-CK model is greater than 0.94, and the mean absolute percentage error (M_MAPE) is within ±17% for all leading times, and the M_MAPE is inside ±10% for leading times within 10 months. Furthermore, the accuracy of the AVMD-GPR-CK is significantly better than those of the commonly used BP, GRNN, RBF, and RELM models.

Accurate load forecasting is of great significance for improving the level of grid planning and accurately guiding investment. In view of the shortcoming of over-fitting in the combined forecasting model of empirical risk minimization, a combined forecasting model based on social learning multi-objective particle swarm optimization algorithm was proposed in term of partial least squares regression model, support vector regression model and grey prediction GM (1, 1) model. The uncertainty function information entropy of weight was introduced to represent the expected risk, and the empirical risk and expected risk were comprehensively considered in the model. The simulation results show that the proposed method has higher prediction accuracy than the single forecasting model and the other two combined forecasting models, and the social learning multi-objective particle swarm optimization algorithm has stronger global search ability and optimization performance.

The deep learning technology was used to study a method of predicting the performance of SCC based on the mixture image information during the mixing process. Twenty-five sets of videos of the SCC mixing process with different performances were recorded. According to the slump flow and T500 measured values and combined with the visual inspection, the SCC mixes were classified into three performances: qualified, insufficient fluidity and segregation. By processing the videos into image sets, the deep learning models were built using image classification and target detection respectively. The models learn and train the image features of the mixes to realize the prediction of SCC performance. The results show that both image classification and target detection methods can achieve more than 98% accuracy on the validation set, which provides a reference for adjusting the mix proportion in real-time and realizing the smart production of SCC.

It is of great significance to explore the variation law of soil thermal conductivity for fields of ground source heat pump systems and soil heat storage. The thermal conductivity variation law of loess and sandy soils with different dry densities and different saturations was investigated by TEMPOS thermal performance analyzer. The results show that saturation and dry density both have significant effects on the thermal conductivity of soil. The thermal conductivity of loess and sandy soil shows an overall increasing trend with the increase of saturation, but there is an obvious difference in the change pattern of thermal conductivity of loess and sandy soil. The thermal conductivity of loess and sandy soil increases with the increase of dry density, but the change range of loess soil is smaller than that of sandy soil. At the same time, 16 prediction models are evaluated based on the experimental data and the results show that the CCM model performs the best.

Roughness is an important parameter which reflects water transport capacity of water diversion project. The roughness value can be calculated by observing the frictional head loss. However, how to estimate the roughness is always a difficult problem in hydraulics for the new unworked water diversion project. The surface roughness of water conveyance buildings is a vital factor affecting the roughness value. So, this study proposed a surface roughness measurement method relies on hierarchical sampling. Taking a new in-situ reinforced concrete lining tunnel as an example, the statistical distribution of surface roughness and the minimum sample size of tunnel roughness estimation were analyzed. On this basis, the roughness value range of the tunnel project was estimated, which has a certain reference significance for predicting the water transport capacity of the new project and inspecting the construction quality of the lining.

Aiming at the cumbersome problem of applying the Markaviev method to calculate the bed-forming flow rate, the geomorphic work diagram method was proposed to simplify the calculation of the bed-forming flow. Based on the measured water and sediment data from 1960 to 2014 at the four hydrological stations of Huayuankou, Gaocun, Aishan and Lijin in the lower reaches of the Yellow River, the Markaviev method and the geomorphological method were used to calculate the bed-forming flow of the four stations over the years. The results show that the differences in the bed-forming flow over the years at the four stations in the lower reaches of the Yellow River calculated by the two methods are small and the downward trend is similar. Compared with the Markaviev method, the geomorphic work diagram method is more convenient and accurate to calculate the bed-forming flow.

sedimentation basin is one of the important water conservancy facilities to reduce the sand content of water flow in agricultural irrigation projects, which plays an important role in reducing the sand content of water flow and improving the utilization rate of water flow. In order to improve the efficiency of sand sedimentation basin discharge, a linear sand collection culvert structure was designed based on the S-type structure of the sedimentation basin in the Weigan River dry canal. The hydraulic characteristics of the S-type and linear sand collection culvert water flow were clarified by combining the experimental results of prototype observation with physical model tests and numerical simulations. The experimental results show that Fluent software can effectively simulate the operation process of local sand traps; Due to the low flow velocity at the end of the S-type sand trap, the sediment accumulation in the sand trap is caused, while the linear structure effectively increases the overall flow velocity in the sand trap, and the flow velocity in the corridor at the end of the sand trap is increased from 0 m/s to 0.4 m/s-0.7 m/s, thus improving the sand discharge efficiency of the sand trap. This study can provide scientific basis and technical support for optimizing the structure of the sand sink and improving the sand discharge efficiency of the sedimentation basin.

In order to realize the remote mobile monitoring of the dam, the automatic identification of important defects and the measurement of key monitoring equipment, the research on the intelligent mobile inspection technology of dam safety based on image recognition technology and track robot was carried out. Firstly, an intelligent mobile inspection system for dam safety was constructed based on the orbital robot. On this basis, the automatic identification of typical dam defects and the measurement of key monitoring equipment were realized based on image recognition technology. It had been applied in a dam with good results. The remote and large-scale inspection of dam safety was realized, which can significantly reduce the workload of manual inspection, replace manual inspection under extreme natural conditions, and timely grasp the operation of hydraulic structures such as dams. The research results can provide important reference and technical support for the safety monitoring of dams.

When the water conveyance tunnel in long-distance water diversion project passes through the potential earthquake area, there is a major engineering safety hazard caused by active fault dislocation. It is of great engineering significance to reveal the influence of fault dislocation on the stability of water conveyance tunnel. Based on ABAQUS finite element analysis software, considering the complex dynamic interaction characteristics of surrounding rock, fault, lining and internal water, the three-dimensional numerical simulation of surrounding rock-fault fracture zone-lining-internal water system was carried out, and the influence of different fault dislocation momentum, width and cohesion on the stability of water conveyance tunnel was analyzed in depth. The results show that the vertical displacement and damage degree of the lining structure of the water conveyance tunnel decrease under the conditions of small fault dislocation, fault width and large fault cohesion, which has a certain reference value for the theoretical study of the dynamic response of the water conveyance tunnel across faults.