Abstract:In order to improve undesirable flow phenomena like spinning and partial flow in forebays of deep tunnel inflow pumping stations, the flow in forebays was numerically simulated based on the RNG k-ε turbulence model, and rectification measures applicable to this kind of urban drainage pumping station were investigated. Numerical simulation results revealed the presence of several adverse hydraulic phenomena within the forebay and inlet pool of the pump station, including local vertical spinning, spiral flow, oblique flow, and uneven velocity distribution with higher velocity at the top and lower velocity at the bottom, resulting in poor hydraulic conditions in the inlet channel of the pump station. A rectification measure combining a double-layer ring plate and two groups of guide piers can suppress the vertical spinning, spiral flow and oblique flow in the forebay and inlet pool. This rectification measure significantly improves the inlet conditions of the flow channel, leading to more uniform flow velocity distribution at the inlet of the inflow channel.Consequently, the pump inflow water conditions become better, and the operation reliability of the pumping station is improved.

Abstract:In order to investigate the hydraulic characteristics of urban drainage pumping stations with curved inlet box culvert and explore the rectification measures to improve the adverse flow state inside the pumping station, the hydraulic flow state and rectification measures of urban drainage pumping stations were studied using the numerical simulation method, and the physical model was used to verify the rectification effect. It is found that the main stream of the forebay in the urban drainage pumping station with curved inlet box culvert is skewed and separated. The main stream of the forebay is concentrated in the middle and upper layers, and there is a large range of facade circulation in the middle and lower layers, and backflow in the bottom layer. The flow in the inlet pool is turbulent and vortices appear, resulting in the water not being able to enter the pump smoothly. The combined rectification measure of square column and combined beam was designed and optimized, and it is found that the combined rectification measure can improve the hydraulic flow pattern of the forebay and the inlet pool. The deviation and separation flow in the forebay are eliminated, the bottom backflow disappears, and the vortex in the inlet pool is effectively suppressed. The uniformity values of the inlet flow velocity distribution of the three water pumps were increased by 12.0%, 8.7%, and 8.3%. The weighted average angles of the inflow velocity were increased by 7.08°, 9.07°, and 11.40°.

Abstract:With the intensification of environmental changes and the rapid progress of science and technology, China’s water disaster prevention and control cause is facing new opportunities and challenges. In order to deeply understand the management and prevention of water disasters, combined with the important needs of national water disaster prevention, the process of water disaster management in China was sorted out and divided into stages, and the necessity of harmonious prevention and control and intelligent simulation research of water disasters (including drought, flood and water environmental pollution) was put forward. Under this background, the research framework of harmonious prevention and control and intelligent simulation of water disasters was put forward from six aspects: guiding ideology, theoretical basis, key issues, research content, application practice and development strategy research, and the future research prospect was put forward from three aspects: theoretical perfection of water disaster prevention and control, research on harmonious prevention and control of water disasters and exploration of intelligent application prospect, with a view to providing business support for water disaster prevention and control and high-quality development.

Abstract:Based on the response process of urban system to flood disaster events, an urban flood disaster resilience evaluation index system consisting of four first-level indicators and 20 second-level indicators was constructed from four aspects: basic resistance, disaster prevention and early warning, emergency response, and adaptation recovery. On this basis, subjective and objective weights were assigned to the indicators through the extension analytic hierarchy process and entropy weight method. Combined with the game theory, a new method of urban flood disaster resilience evaluation based on the combined weighting-cloud model was proposed. The verification results of six administrative districts in Nanjing City show that the method can effectively evaluate the resilience level of urban flood disaster. Among the six administrative districts, Jianye District and Jiangning District are high resilience areas, Gulou District and Qinhuai District are relatively high resilience areas, Yuhuatai District is a medium resilience area, and Lishui District is a relatively low resilience area.

Abstract:Aiming at the problem of data lacking for internal dynamics in landslide surge tests, an improved particle image velocimetry technology was used to build a landslide surge test platform.A viscoplastic material called Carbopol was chosen as the landslide material. Using fluorescence seeding particles, the internal dynamics of the submerged sliding mass and body of water was obtained respectively, and then the velocity field of the two phases was estimated. Using the velocity field data, the evolution of the mass and mean velocity of the submerged sliding mass, as well as the momentum variation of the sliding mass and body of water were calculated and analyzed. The results show that there is a high correlation between the momentum change trend of landslide and water body and the momentum of landslide body entering water, providing more complex and multivariate data support for the theoretical research of momentum transformation mechanism of two-phase coupling.

Abstract:In order to explore the simulation and calculation of a water hammer with liquid column separation, a new cavity model was proposed based on the improvement of a discrete vapor cavity model (DVCM). The non-full flow pattern in the cavity was considered in the new cavity model, and according to the flow state of the upstream and downstream sections, the calculated sections were divided into seven types. Calculation modules were established to calculate the classified cavity sections and the transient process of the cavity was simulated more accurately.The new model was preliminarily verified by simple pipeline and complex pipeline tests. The results show that compared with the traditional DVCM, the new cavity model can more accurately predict the pressure fluctuation, cavity shape, location and volume change in the transient flow.The simulation of the peak pressure fluctuation in the process of water column bridging is closer to the measured data, which helps to guide the safety protection of water hammer in engineering.

Abstract:Aiming at the problem of high energy consumption and sludge deposition that could occur in oxidation ditch sewage treatment technology, the viscosity and settling rate of activated sludge was imported into Fluent software through a user-defined function, and then the numerical simulation for water-activated sludge two-phase flow calculation of standard oxidation ditch in a sewage treatment plant was conducted. The power of thruster, the distribution of velocity and sludge in the oxidation ditch could be obtained. Compared with each other, the optimal motor power and velocity distribution was selected. The flow field characteristics of the oxidation ditch were further analyzed and compared the section flow velocity obtained by numerical simulation with the experiment measurements, showing that the data from the measuring points has good performance of consistency, and the velocity of each point in the real flow field can be well predicted by numerical simulation. The sludge mass concentration is generally higher in the area with high velocity dead zone rate.

Abstract:The water demand data of various water use industries in Zhejiang Province from 2000 to 2020 were collected, and the main driving factors affecting the water demand of each industry were screened using the main driving factor screening method based on Spearman rank correlation analysis. An improved long short-term memory (LSTM) neural network water demand prediction model was constructed to make dynamic rolling forecasts of the water demand of each industry, and the prediction results of the improved LSTM model were compared with those of the traditional univariate LSTM prediction model, convolutional neural network (CNN) model, and support vector regression (SVR) model. The results show that the LSTM model improved by the principal driving factor screening method can predict the annual water demand of each industry in real time and dynamically, and the prediction accuracy of the improved model is higher than that of the other three models.

Abstract:Based on the water ecology survey results of 24 major drinking water sources in Fujian Province in the summer of 2021, the characteristics of phytoplankton community structure and nutrient status of reservoirs were analyzed. The phytoplanktonic index of biotic integrity (P-IBI) was constructed using three biological parameters, total phytoplankton density, Shannon-Wiene diversity index, and proportion of cyanobacteria density to evaluate the health status of the Shaxikou Reservoir and the Dongzhang Reservoir. The results show that the phytoplankton community structure of most reservoirs in Fujian in 2021 was dominated by Cyanophyta-Chlorophyta-Bacillariophyta, and 60.9% of the reservoirs were dominated by Cyanobacteria. The comprehensive nutrient status index ranged from 24.3 to 51.7, with an average value of 40.3. The eutrophication degree of reservoirs was low, but some reservoirs still had the risk of eutrophication. The P-IBI score of the Shaxikou Reservoir was 79.7, which was in a healthy state, while the P-IBI score of the Dongzhang Reservoir was 59.0, which was in a sub-healthy state. The evaluation results of P-IBI are in good agreement with the results of the multi-index evaluation method in the Blue Book of River and Lake Health Assessment of Fujian Province in 2021 . The evaluation method based on phytoplankton integrity index is effective and applicable.

Abstract:In order to analyze the impact of rectification of water conveyance structures on the water diversion capacity of the Middle Route Project of the South-to-North Water Diversion Project, taking the section from the gate of Taocha canal to the Shierlihe aqueduct as an example, a coupled one- and two-dimensional hydrodynamic model was established, with the one-dimensional model adopted for the channel section and the two-dimensional model adopted for the sections of the four water conveyance structures (the Diaohe aqueduct, Tuanhe aqueduct, Yanlinghe aqueduct and Qihe inverted siphon). The coupled model was calibrated with multi-year measured data. Fifteen rectification schemes and a scheme without rectification were simulated to analyze the impact of different schemes on the upstream and downstream sections and to explore the rectification scheme with the minimum head loss. The results show that the impact range of rectification is from 3 to 5 km upstream and downstream of a single structure and the cumulative effect of multiple structures is less than that of the linear superposition of single structures. The effect of rectification of the two water conveyance structures (the Tuanhe aqueduct and Yanlinghe aqueduct) in the middle of the channel section is better than that of the two water conveyance structures (the Diaohe aqueduct and Qihe inverted siphon) in the upstream and downstream sections.

Abstract:To overcome the limitations of existing methods for diagnosing the deformation state of high arch dams, a new diagnosis method was proposed considering the progressive failure characteristics of the deformation instability process. The method combines modern dam engineering, mechanics and mathematical theories. The elastic deformation state of high arch dams was calibrated based on the characterization of water pressure, temperature change, and time-dependent deformation. The individual diagnostic index was established using the information entropy theory. According to the projection pursuit method, the individual contributions were optimally achieved, and then the group diagnostic index was built. The diagnostic control values were constructed based on the typical small probability principle. On this basis, the diagnostic criteria of group normality, group basically normality, individual abnormality, group abnormality, and group deterioration were developed. Engineering example results indicate that the established method can effectively characterize the progressive failure process, and it is applicable to the situation that the most unfavorable load has not been encountered yet.

Abstract:Aiming at the problems of local optimality, poor interference resistance, and low prediction accuracy of the traditional seepage monitoring model for earth-rockfill dams, through optimization of the Extreme Gradient Boosting (XGBoost) algorithm (RUN-XGBoost algorithm) by the Runge Kutta optimizer (RUN) algorithm, a RUN-XGBoost model was constructed to obtain better seepage prediction results.The RUN algorithm is applied to improve the three main parameters of the XGBoost algorithm during the initialization of the population, which gives high validity to the prediction results.The overall convergence speed and prediction accuracy of the algorithm are improved by automatic searching for the optimal parameter.A stochastic variance factor is also introduced to enable the algorithm to exclude local minima and continue the search to obtain a globally optimal result.The validation results of engineering examples show that the RUN-XGBoost model has the advantages of simplicity, high efficiency, high prediction accuracy and robustness.

Abstract:To efficiently, accurately, and automatically achieve the optimized design of hollow structures, a chamber retaining wall was taken as the research object.Parametric modeling based on Python and ABAQUS was carried out, and the automation for the whole process of modeling, finite element calculation and analysis was realized. Combined with a chamber retaining wall in a sluice project, the multi-objective optimization design under multiple constraints was carried out by using non-dominated sorting genetic algorithm (NSGA-Ⅱ algorithm), aiming at the optimal of several strength and stability indexes and the minimization of concrete volume by taking the index threshold, geometric size and volume requirement as constraint conditions. In order to further improve the computational efficiency, a surrogate model was established based on artificial neural network algorithm, which could achieve a highly approximation to the actual finite element model. The results show that the proposed optimization process for chamber retaining walls can minimize concrete usage while effectively controlling strength and stability, and has significant economic benefits.

Abstract:Based on the results of large-scale dynamic triaxial tests on coal gangue subgrade fillers, the grey correlation analysis method was used to analyze the influencing factors of cumulative deformation, and four characteristic parameters were determined, including confining pressure, compactness, gradation, and cyclic loading number. The particle swarm optimization (PSO) algorithm was used to globally optimize and assign the weights and thresholds of the back propagation (BP) neural network, and a PSO-BP neural network prediction model for cumulative deformation of coal gangue subgrade fillers was established. By comparing the traditional BP neural network with the established prediction model, the feasibility and superiority of the established prediction model were verified. The generalization ability of the model was further analyzed by comparing the prediction effects of the model under different learning levels, which proved the prediction potential of the model.

Abstract:Aiming at the problem of poor pre-processing of monitoring data of dangerous rock mass in the past, a VMD-XGBoost-GRU combined model was proposed for predicting deformation of dangerous rock mass. The model firstly uses variational mode decomposition (VMD) and sample entropy theory to decompose the deformation data of dangerous rock mass into multiple sub-sequences, then uses extreme gradient lift (XGBoost) algorithm to extract important model factors to achieve feature dimensionality reduction, and finally predicts the deformation of dangerous rock mass through gated recurrent unit (GRU) neural network. Taking the dangerous rock mass on the steep wall of the right abutment of a hydropower station as an example, the VMD-XGBoost-GRU combined model was compared with three other models, namely BP, GRU and VMD-XGBoost-BP. The results show that the VMD-XGBoost-GRU combined model has high precision in predicting the deformation of dangerous rock mass, and can provide technical basis for the evaluation of the safe and stable state of dangerous rock mass.