[Objective] Rapid prediction of rainstorm waterlogging is crucial for disaster prevention and reduction. However, the traditional numerical models for simulating and predicting large-scale and complex subsurface conditions are complicated and time-consuming; moreover, the time-efficiency requirement of rainstorm waterlogging prediction is difficult to meet. To address these shortages of the numerical models, this study constructs a spatiotemporal prediction model of urban rainstorm waterlogging based on machine learning methods to rapidly predict waterlogging extent and water depth changes.[Methods] This study constructs a rapid prediction model of urban rainstorm waterlogging based on a hydrodynamics model and machine learning algorithms. First, a hydrodynamic model is constructed based on InfoWorks integrated catchment management (InfoWorks ICM) for rainstorm waterlogging in the study area with the parameter rate determination and model validation to realize the high-precision simulation of urban rainstorm waterlogging. On this basis, a rainfall scenario-driven hydraulics model is designed to further obtain rainstorm waterlogging simulation results. These results are used as the base dataset for machine learning. Second, the spatial characteristics data of rainstorm waterlogging are obtained from three aspects: rainfall situation, subsurface information, and the drainage capacity of the pipe network, which, together with the grid simulation results, comprise the dataset. The spatial prediction models are based on random forest, extreme gradient boosting (XGBoost), and K-nearest neighbor algorithms. Finally, the simulation results of waterlogging points are used to generate rainstorm waterlogging time series data. The rainfall, cumulative rainfall, and water depth of the first four moments (every 5 min) are used as the input for a long short-term memory (LSTM) neural network to predict the present water depth of the flooding point. The two models collaborate to achieve rapid spatial and temporal predictions of urban rainstorm waterlogging.[Results] For spatial predictions, the random forest model has the best fitting performance regarding evaluation indexes such as the mean square error, the mean absolute error, and the coefficient of determination (R²). When a rainstorm scenario with an 80-year event and a 2.5 h rainfall calendar prediction set is used, the prediction results concur with the risk map of urban waterlogging in Beijing. Compared with the simulation results of InfoWorks ICM, the prediction accuracy of the predicted inundation extent reaches 99.51%, and the average prediction error of waterlogging depth does not exceed 5.00% by the random forest model. For temporal predictions, the trend of the water depth change of the LSTM neural network model is more consistent with the simulation results of InfoWorks ICM, the R² of four typical inundation points are above 0.900, the average absolute error of water depth prediction at the peak moment is 1.9cm, and the average relative error is 4.0%.[Conclusions] When addressing sudden rainstorms, the rapid prediction model based on machine learning algorithms built in this study can generate accurate prediction results of flooding extent and water depth in seconds by simply updating the forecast rainfall data in the model input. The model computational speed is greatly improved compared to the hydrodynamics-based numerical model, which can help plan waterlogging mitigation and relief measures.

[Objective] Rail corrugation is a problem that needs to be addressed urgently and is one of the common technical issues limiting the development of contemporary rail transit. This study uses the finite element method to analyze the formation process of rail corrugation from the wheel-rail transient contact stick-slip vibration to provide new insights into the mechanism of rail corrugation and to understand the phenomenon of rail corrugation on the metro line. [Methods] This study examines the formation mechanism of rail corrugation using field measurements and numerical simulation. First, according to the on-site corrugation situation, a three-dimensional wheel-rail rolling contact model is developed using the finite element software ABAQUS, and its effectiveness is established. The contact stick-slip state is then analyzed during the wheel operation, and the influence of the rail surface and no rail surface defect on it is discussed. Furthermore, the relationship between stick-slip characteristics and corrugation formation is examined. Finally, the inherent characteristics of the wheel-track system and longitudinal wear characteristics of rail are analyzed using the complex modal theory and the Archard wear model to explain the formation mechanism of rail corrugation. [Results] The results revealed that when the wheel rolled over the smooth rail, the adhesion area was at the front edge of the contact area, and the middle and rear edges were the slip area, which was closer to the steady state dynamic calculation results, verifying that the established finite element model was effective. Moreover, the wheel-rail contact was always in a stable rolling state, indicating that the wheel-track system was not easily unstable, consequently making corrugation generation difficult. When the wheel rolled through the squat defect, the contact area was shown as two slip areas surrounding the squat; after the wheel rolled through the squat defect, the area of the wheel-rail contact patch decreased, and almost all of it showed slip. The squat defect changed the stick-slip state of wheel-rail rolling contact and promoted the slip of the wheel-rail interface, which induced the instability of the wheel-track system and caused the wear of the rail surface material; this might eventually form rail corrugation. The complex modal analysis showed that the rail surface defect exacerbated the inherent unstable vibration characteristics of the wheel-track system, and the unstable vibration frequencies fell within the measured corrugation passing frequency range. [Conclusions] The analysis results of wheel-rail contact stick-slip and complex modal reveal that the formation mechanism of rail corrugation can be attributed to the inherent unstable vibration of the wheel-track system caused by the excitation of the rail surface defect, and the unstable vibration is represented by the vertical bending vibration of the rail relative to the track slab. Thus, when the wheel passes through the squat defect, it will stimulate the transient fluctuation wear, which results in wavy wear on the rail surface. The characteristic wavelength of the longitudinal wear on the rail surface is 40～50 mm, which is consistent with the corrugation wavelength on the actual line; thus, the formation mechanism of rail corrugation is further validated in the process of quantifying rail corrugation formation.

[Objective] Considering the advancement in underground space construction in China, the number of single-end tunnels during the construction process has increased annually. To study the smoke-spreading characteristics of fires occurring in single-end tunnels formed during subway construction, a full-scale experiment was performed in the construction section of a subway tunnel.[Methods] The diffusion and settlement laws of smoke in a single-end tunnel were studied through the analysis of the overall temperature distribution, wind speed distribution, smoke layer height, and other tunnel parameters with on-site observation combined.[Results] The results indicate that under natural ventilation, the diffusion velocity of smoke is slower toward the closed end than toward the through end; moreover, the velocity difference decreases with increasing distance between the ignition source and the closed end.[Conclusions] The decay rate of ceiling flue gas temperature is slower toward the through end than toward the closed end. The distribution of flue gas at the connected end conforms to the classical model with the exponential decay distritution, while the closed end has a clear accumulation effect, forming a dangerous section. The height of the flue gas layer at the closed end is as low as 1.5 m, which is the key aspect for consideration in flue gas control and fire emergencies.

As a novel ocean exploration robot, an underwater glider can achieve space motion by adjusting its net buoyancy and attitude. In some exploration missions, the underwater glider must reach a specific location for virtual mooring and perform a fixed-point exploration, including the health monitoring of underwater equipment. The typical research aim is for the glider to reach the target exploration area at the earliest by consuming the minimum possible energy. To achieve this goal, the optimal control parameter configuration of the underwater glider must be determined. Therefore, this paper proposes the control parameter optimization method of underwater gliders for fixed-point exploration missions based on the dynamic theory, surrogate model technology, and multi-objective optimization algorithm. First, considering a typical underwater glider as the research object, this paper establishes the whole glider dynamic model using the Newton-Euler method. This dynamic model contains eight degrees of freedom and considers the effects of seawater density variation and hull deformation on the glider's net buoyancy. Considering the energy consumption of buoyancy adjustment, attitude adjustment, control, and measurement systems, the energy consumption model of the glider diving motion is established. On this basis, the sample points are obtained using an optimal Latin hypercube experimental design and dynamic simulation, and subsequently, the surrogate models are established using a quartic polynomial to fit the obtained sample points. Here, the input parameters of the quartic polynomial are the amounts of glider net buoyancy adjustment and movable internal mass block translation, and the output parameters are the energy consumption, diving motion time, and horizontal displacement of the glider to reach the target depth. Next, a mathematical optimization model is proposed. Specifically, the glider control parameters are selected as the optimization design variables; the optimization objective is to minimize the glider energy consumption and the diving motion time, simultaneously, and the horizontal displacement is used to construct the constraint. The surrogate models are employed to participate in the optimization calculation, which can improve the calculation efficiency. Finally, the non-dominated sorting genetic algorithm II is used to solve the abovementioned optimization problem. A numerical example is provided to validate the proposed optimization method. After optimization calculation, the Pareto optimal set is obtained, consisting of 74 sets of non-dominated solutions of control parameter values. The analysis results illustrate that once the target depth has been determined, the glider horizontal displacement shows an obvious difference under different control parameter values, implying that the glider can employ different control parameter configurations to perform underwater fixed-point exploration missions. Under a specific target depth, the quartic polynomial can accurately describe the mapping relationship among the net buoyancy adjustment amount, movable internal mass block translation amount, glider energy consumption, diving motion time, and horizontal displacement. Besides, the functional relationship between the glider control and performance evaluation parameters shows obvious nonlinearity and nonmonotonicity. Optimization results of the control parameters demonstrate a contrasting relationship between the energy consumption and the diving motion time of the glider. For practical engineering missions, the selection rule of the optimal solution is listed, and the optimization results are verified via dynamic simulation. On the basis of the dynamic theory, surrogate model technology, and multiobjective optimization algorithm, the proposed optimization method exhibits high calculation efficiency and can be used for guiding the glider control parameter configuration in actual fixed-point exploration missions. Besides, this optimization method is versatile and can be used in various types of underwater gliders.

[Objective] Seismic damage and destruction of the stations, tunnels, and other structures considerably impair the functionality of the urban rail transit system. Current research on the system performance of the rail transit network primarily focuses on the scenarios of intentional attack and stochastic damage, which is dramatically different from the earthquake disaster scenarios. This paper proposed a quantitative framework to evaluate the seismic performance and resilience of rail transit networks. [Methods] The seismic fragility model was used to calculate the failure probability of the primary structural elements, including stations, tunnels, and bridges of the rail transit system. The graphical model of the network was established using the Space L modeling method. This approach was used to depict the interdependency of system elements. The network performance was expressed by the network efficiency weighted by passenger flow between rail transit stations. The Monte Carlo simulation was used to assess the uncertainty of the earthquake damage state of structures and the post-earthquake recovery of the damaged elements. According to the network performance curves during the post-earthquake recovery process, the seismic resilience index and resilience loss of the rail transit network were quantitatively evaluated using the concept of resilience triangle. Considering the Beijing rail transit network, the effects of earthquake intensity, recovery strategy on network performance, and resilience indexes were investigated. [Results] The results of the present analysis were as follows. (1) The resilience characteristics of rail transit networks under earthquakes, intentional attacks, and stochastic damage were different. The resilience index under earthquake damage was 0.936 3, whereas the resilience index under stochastic damage was 0.934 0. The resilience index under intentional attack was 0.863 4. (2) In the damage scenario corresponding to different earthquake intensities, the system resilience index calculated by the recovery sequence sorted by the dynamic importance of damaged elements were larger than that sorted by the static importance of damaged elements. Moreover, the damage scenario involving several damaged elements typically results in a larger difference between the resilience index calculated by the two recovery strategies. (3) Pre-earthquake enhancement measures to reduce the failure probability of crucial elements could effectively enhance the disaster resistance capacity of the network; however, their influence on improving the post-earthquake recovery capacity remained unclear. [Conclusions] Based on the seismic fragility models of the primary structure of the rail transit network, the graphical model of the network, and the importance of ranking-based post-earthquake recovery of the damaged elements, this paper establishes a framework to quantitatively evaluate the seismic resilience of rail transit network by the passenger-weighted network efficiency. When evaluating network resilience and comparing antiseismic improvement measures, multiple indicators such as resilience index, resilience loss, and recovery duration should be comprehensively analyzed. This framework can provide a reference for the seismic performance evaluation of the urban rail transit network and help decision-makers in allocating maintenance resources to restore the operation function of the urban rail transit system in a timely and cost-effective manner during the recovery process.

[Objective] In recent years, a large number of nonconvex, highly nonlinear, multimodal, and multivariable complex optimization problems have emerged in scientific and engineering technology design due to the continuous development of science and technology. Owing to their advantages such as simple programming, flexible operation, and efficient optimization, intelligent optimization algorithms have become research hotspots to address diverse complex optimization problems in engineering applications. They have been successfully used to solve practical problems such as neural networks, resource allocation, and target tracking. In this research, multiple strategies were developed to improve the existing monarch optimization algorithm to address its shortcomings, such as slow convergence speed, low optimization accuracy, and ease of falling into local extremum. [Methods] First, the forward normal cloud generator is used to perform nonlinear cloud operation on the parent monarch butterfly, increasing the number of candidate solutions and improving the local development ability of the algorithm. Subsequently, an opposition-based learning strategy based on convex lens imaging is used to the current optimal individual which is generated by normal cloud generator to generate new individuals and improve the convergence accuracy and speed of the algorithm. Finally, adaptive strategies are incorporated into the adjustment operator to diversify the population. [Results] Several experiments were performed on benchmark functions to verify the performance of the algorithm: (1) Different strategies proposed were analyzed using ablation experiments to verify their effectiveness. The results revealed that the proposed strategies can effectively improve the algorithm's performance. (2) The improved algorithm was compared with other swarm intelligent optimization algorithms, and the results revealed that the improved algorithm can achieve the best results on most test functions. (3) The improved algorithm was also compared with other improved versions of monarch optimization algorithm, and the results revealed that the improved algorithm exhibited more advantages such as fast convergence speed and high convergence precision. (4) The Wilcoxon rank sum test and Friedman test were used to verify the performance of the proposed algorithm. The results revealed that the improved algorithm is superior to other algorithms. [Conclusions] The optimization and comparison results of the pressure vessel design and welded beam design in engineering applications further verified the superiority of the improved algorithm in addressing real-world engineering problems.

[Objective] The assembly of spacecraft components plays an important role in their production, and the quality and efficiency of assembly have a direct impact on the quality and efficiency of their production. Currently, spacecraft components are often constructed by hand, which results in low accuracy and efficiency. The aerospace industry's research focus is on utilizing robots to complete the assembly tasks of spacecraft components, which can improve the quality and efficiency of their production. The current assembly robots mostly use the position control mode, which measures the relative pose between the assembly features of two spacecraft components and then moves the robot to complete the robotic assembly tasks according to the measurement results. In this control mode, assembly errors are unavoidable due to measurement and robot motion errors, which will result in a huge contact force between the two contact surfaces of the spacecraft components. Excessive contact forces can damage the surface quality and coatings of spacecraft components, ultimately affecting their service lives. Therefore, the contact forces are required to be controlled by compliance control. The control parameters in the current study of compliance control are established based on the operator's experience, which is closely related to the contact forces. Because the spacecraft components are manufactured in small batches, pre-assembly cannot be used to determine the control parameters without damaging their surface quality and coatings. And improper control parameters can lead to uncontrolled contact forces. [Methods] To address this issue, a compliance control method is proposed in this paper based on the classical admittance control, which can adaptively adjust the control parameters according to the contact forces and system status. In this adaptive compliance control, the target pose and stiffness matrix are changed during the assembly process. This research examines the control effects of adaptive compliance, position, and classical admittance controls to validate the practicality of this strategy. Taking the control moment gyroscope (CMG) assembly task as an example, this research designs and develops a CMG robotic assembly prototype. The F/T sensor is installed between the CMG and the robot's end-effector to measure the contact forces during the assembly process. And Kalman filtering is utilized in this paper to filter the measurement noise of the F/T sensor. [Results] The position and orientation of the CMG were modified according to the adaptive compliance control presented in this study. After adjusting the position and orientation, the CMG's contact surface and the mounted base's contact surface were fitted together, and the contact forces of the two surfaces were guaranteed to be small. [Conclusions] The outcomes of the simulation and experiment results show that adaptive compliance control has advantages, including fast convergence, minimal residual contact force, and adaptive adjustment of the control parameters. Additionally, the adaptive compliance control suggested in this study can be quickly applied to various spacecraft component assembly tasks. This method establishes the theoretical and technical foundation for autonomous robotic assembly of spacecraft components and is expected to be employed for real-world spacecraft component assembly tasks.

The grounding grid plays a vital role for ensuring reliable power system operations. However, the buried environment around the grounding grid can result in grounding device defects, so the grounding grid must be periodically tested. This paper presents a SH guided wave detection method based on linear frequency modulation excitation and synchrosqueezed wavelet transforms for grounded flat steel power systems. The system uses a permanent magnetic array SH guided wave transducer which is simple and suitable for flat steel structures. The transducer is excited with a linear frequency modulation signal with synchrosqueezed wavelet transforms used to analyze the signal. Identification of the overlapping guided wave signals in the time-frequency plane effectively distinguishes between various defects and end faces. Signals from finite element simulations and experiments were then used to evaluate the signal analysis method. The calculated distance errors were all within 3%, which shows that the method can accurately extract the guided wave travel times and accurately locate defects. Comparisons with results using short-time Fourier transforms and Wigner distributions show the advantages of the time-frequency aggregation of the synchrosqueezed wavelet transforms.

Vane pumps convert mechanical energy into fluid energy with the impeller being the key component. This paper designed a flow pump impeller using iterative solutions of direct and inverse problems. The velocity moment distribution along the axial streamline is controlled by a quartic function determined by the midpoint and outlet slope of velocity moment. Analyses of the influence of the velocity moment distribution on the impeller performance show that increasing the midpoint of velocity moment increases the load from the blade inlet to the middle which improves the pump work. The midpoint of velocity moment mainly affects the relative velocity distribution near the blade tip and the axial velocity in the middle of the impeller. The design was evaluated in energy and cavitation experiments. The high-efficiency operating range of the pump is flat and wide with a highest efficiency of 82.17%. The cavitation specific speed is 1 289.

[Objective] Spontaneous coal combustion is one of the major natural disasters in coal mining; thus, accurate prediction of the risk of spontaneous coal combustion is crucial to prevent and control coal fire disasters. However, the complexity of the physicochemical process of spontaneous coal combustion and its various influencing factors poses a challenge to the risk prediction of spontaneous coal combustion. Strengthening research on spontaneous coal combustion hazard prediction technology using deep learning is crucial for improving the intelligent control level of coal mine safety production.[Methods] In this study, CO volume fraction was chosen as the index for spontaneous coal combustion evaluation. A dataset was constructed, and the field observation data were visualized. Next, the dataset was tested for the distribution of eigenvariables, normalized for the distribution of eigenvariables, and normalized for the dataset using kernel density estimation, logarithmic transformation, and maximum-minimum normalization. Finally, three algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM) network, and gated recurrent unit (GRU), were applied to the data mining of spontaneous coal combustion feature information, and a dynamic sequence prediction model of spontaneous coal combustion CO volume fraction was established. During the model construction process, the full connectivity layer and Dropout class were added to prevent overfitting, and the mean square error and three model performance test indicators were introduced to analyze and optimize the model parameters and test the model performance.[Results] The results were presented as follows:(1) The CO volume fraction sequence dataset was established based on the field data of the Dafosi Coal Mine, the model generalization capability was enhanced, and the training time of the model was shortened by preprocessing the dataset. (2) The RNN, LSTM, and GRU models achieved the dynamic prediction of CO with an error of less than 1 %. (3) The optimal parameters of the three models were determined from the mean absolute error (MAE), the root mean square error (RMSE), and R² of the training and validation sets. A comparative study using the model performance evaluation metrics revealed that the LSTM model had the highest prediction accuracy under the same sequence data, followed by the RNN and GRU models.[Conclusions] Using 285 sets of field data, the spontaneous coal combustion CO volume fraction sequence prediction models based on the RNN, LSTM, and GRU algorithms were established. The experimental values of the CO volume fraction were highly consistent with the predicted values, and the prediction error was less than 1 %. The model can predict the change in the CO volume fraction in future moments using the dataset. The results reveal that the dynamic time series prediction of CO volume fraction from spontaneous coal combustion using sequence models is possible compared with conventional static models. Moreover, the process of constructing the three models and optimizing the parameters can be employed as a basic study for developing sequence prediction models for other indicator gases.

[Objective] Formations of fixed-wing unmanned aerial vehicles (UAVs), which are commonly used in military, rescue, and other missions, often do not have the ability to hover and have a large turning radius. Thus, when operating in an unknown environment, it is easy for the formations to collide in the presence of obstacles, which will gravely affect flight safety if not guarded against. It is difficult to avoid unknown environmental obstacles using traditional modeling methods. However, artificial potential field methods can address deadlock problems such as target infeasibility and cluster congestion. [Methods] To achieve the cooperation of UAV formations without collision, a deep deterministic policy gradient (DDPG)-based centralized UAV formation control method is proposed in this study, which is designed by combining the centralized communication architecture, reinforcement learning, and artificial potential field method. First, a greedy-DDPG flight control method is studied for leader UAVs, which improves collision avoidance effectiveness. Considering maneuver constraints, reward functions, action spaces, and state spaces are improved. Additionally, to shorten the training duration, the exploration strategy of DDPG is improved using the greedy scheme. This improvement mainly uses the critic network to evaluate the value of random action groups and improves greedy selection to make actions more inclined, thus achieving rapid updates regarding the critic network and accelerating the update of the overall network. Based on this, incorporated with the artificial potential field method and leader-follower consensus, a collision-free control method is designed for followers, which can ensure collision-free following cooperation. [Results] The numerical simulation experimental results show that the improved DDPG algorithm has a 5.9% shorter training time than the original algorithm. In the same scenario, the method that we proposed perceives the same number of obstacles as the artificial potential field method. The artificial potential field method has significant fluctuations in heading angle, while the proposed method has relatively small fluctuations. The DDPG algorithm has a smoother heading angle due to a smaller number of perceived obstacles; however, the minimum distance from the obstacles is only 9.1 m. The method that we proposed here is above 17 m from the obstacles. Furthermore, Monte Carlo experimental data under different scenarios of the long aircraft show that the ability of obstacle avoidance generalization of the proposed method is improved. Moreover, experiments were applied to the proposed formation control method. Under the same scenario and control parameters, the UAV formation control method based on the proposed architecture has lower formation errors during flight, with a maximum error of no more than 10 m. However, the artificial potential field-based formation control method has a maximum formation error of over 25 m. When encountering narrow gaps, our proposed method can quickly pass through without congestion, while the artificial potential field-based formation control method appears to hover in front of obstacles, which is not conducive to flight safety. During the entire flight, this method has a greater distance from obstacles and higher safety. [Conclusions] Compared with the original DDPG algorithm, the improved DDPG algorithm has faster training speed and better training effect. The formation control method can realize the formation flight of unmanned aerial vehicles under unknown obstacles. Compared with the formation control method based on artificial potential field, the formation control method avoids the hovering in place before obstacles, which is of great significance to the formation flight safety of unmanned aerial vehicles.

[Objective] The research on soil salinization is complicated, and the traditional literature review method struggles to grasp the development trend systematically due to its subjective nature. Hence, it becomes important and necessary to seek alternative methods to objectively summarize and analyze the existing research papers and reasonably guide the future development of this field. [Methods] Based on the quantitative analysis of the Web of Science and China's national knowledge network databases related to soil salinization and saline-alkali land management and its utilization in the past 30 years, this paper proposes a quantitative review method for obtaining the research trend in this subject. This paper uses various software tools, including VOSviewer, Citespace, and SPSS, to analyze the number of publications, cooperation networks, and keywords within this field. [Results] The results show a continuous increase in the research on soil salinization at home and abroad. The number of scholars participating in the study of soil salinization has also increased significantly. The primary stage of development was before 1999, the stage of stable development was from 2000 to 2011, and the stage of rapid development was from 2012 to the present. Despite significant progress, according to Kuhn's model, the field remains in the primary science stage, indicating ample room for development. English journals such as Agricultural Water Management and Science of the Total Environment and Chinese journals such as Soil Bulletin and Soil can be regarded as core journals in the field of soil salinization, with the highest number of publications and higher journal impact factors. China, the United States, India, Australia, and other countries (in order of the number of papers published by them) have made outstanding contributions to soil salinization research, with Chinese scholars leading in terms of the highest number of published papers and are the main force in the study of soil salinization. The cooperation network analysis shows the importance of research institutions and direct government agencies in promoting institutional cooperation. However, at present, most cooperations are limited to intra-institutional cooperation, but future efforts should focus on the positive impact of cross-context, cross-institutional, transnational, and interdisciplinary cooperations on leapfrog and diversified development of soil salinization research. Keyword burst detection shows that "biochar", "yield", "salt stress", "quality", "freeze-thaw cycle" and "water and salt transport" are the recent hot spots of concern. Additionally, keyword co-occurrence and trend analyses show the shift in research focus from irrigation and drainage and saline-alkali land improvement in the 1990s to soil-plant salt interaction mechanism, salt-tolerant plant cultivation, soil water and salt regulation mechanism, optimization control technology, research and development technology of saline-alkali soil amendment, large-scale applications, remote sensing monitoring of saline-alkali land, and salinization impact assessment. It represents the developmental trend of research on soil salinization and saline-alkali land management and its utilization from drainage improvement to comprehensive utilization. [Conclusions] The research results of this paper quantitatively highlight the research hotspot and developmental trend of soil salinization and provide a reference for relevant researchers to grasp the developmental trends of the field and explore valuable new research directions.

[Significance] Since the turn of the 21st century, artificial intelligence (AI) has advanced considerably in many domains, including government affairs. Furthermore, the emergence of deep learning has taken the development of many AI fields, including natural language processing (NLP), to a new level. Language models (LMs) are key research directions of NLP. Referred to as statistical models, LMs were initially used to calculate the probability of a sentence; however, in recent years, there have been substantial developments in large language models (LLMs). Notably, LLM products, such as the generative pretrained transformer (GPT) series, have driven the rapid revolution of large language research. Domestic enterprises have also researched LLMs, for example, Huawei’s Pangu and Baidu's enhanced language representation with informative entities (ERNIE) bot. These models have been widely used in language translation, abstract construction, named-entity recognition, text classification, and relationship extraction, among other applications, and in government affairs, finance, biomedicine, and other domains. [Progress] In this study, we observe that improving the efficiency of governance has become one of the core tasks of the government in the era of big data. With the continuous accumulation of government data, traditional statistical models relying on expert experience and local features gradually suffer limitations during application. However, LLMs, which offer the advantages of high flexibility, strong representation ability, and effective results, can rapidly enhance the intelligence level of government services. First, we review the research progress on early LMs, such as statistical LMs and neural network LMs. Subsequently, we focus on the research progress on LLMs, namely the Transformers series, GPT series, and bidirectional encoder representations from transformers (BERT) series. Finally, we introduce the application of LLMs in government affairs, including government text classification, relationship extraction, public opinion risk identification, named-entity recognition, and government question answering. Moreover, we propose that research on LLMs for government affairs must focus on multimodality, correctly benefit from the trend of “model as a service,” focus on high data security, and clarify government responsibility boundaries. Additionally, a technical path for studying LLMs for government affairs has been proposed. [Conclusions and Prospects] The application of LLMs in government affairs mainly focuses on small-scale models, lacking examples of application in large-scale models. Compared with smaller models, large models offer many advantages, including high efficiency, broader application scenarios, and more convenience. These advantages can be understood as follows. In terms of efficiency, large models are usually trained on a large amount of heterogeneous data, thus delivering better performance. In terms of application scenarios, large models gradually support multimodal data, resulting in more diverse application scenarios. In terms of convenience, we emphasize the “pretraining + fine-tuning” mode and the invocation method of interfaces, making LLMs more convenient for research and practical applications. This study also analyzes the issues suffered by LLMs, specifically from the technological and ethical perspectives, which have resulted in a panic to a certain extent. For example, ChatGPT has generated many controversies, including whether the generated files are novel, whether using ChatGPT will lead to plagiarism and ambiguity as to who are property rights owners for the generated files. Overall, it can be said that LLMs are in the stage of vigorous development. As the country promotes research on AI and its application in government affairs, LLMs will play an increasingly crucial role in the field.

[Objective] The atmosphere-breathing electric propulsion (ABEP) system has become a highly promising candidate for drag compensation in spacecraft operating in very low Earth orbit. To improve the inlet design of ABEP systems, this study performs a comprehensive numerical investigation of gas flows inside the inlet. The primary objective is to gain insight into the effects of the gas-surface interaction (GSI) model on the flow features, compression, and collection performances. [Methods] This paper explores ABEP inlet flows using the direct simulation Monte Carlo (DSMC) method. A typical altitude of 180 km in the upper atmosphere is considered, and four GSI accommodation coefficients (σ=1, 0.8, 0.5, and 0.2) are selected. The DSMC method simulates gas flows according to the motion of a cluster of simulation particles, where each particle represents a large number of real gas molecules. In the DSMC method, particle motions are computed deterministically, whereas intermolecular collisions are calculated statistically. Each simulation particle travels at a constant velocity until it collides with another simulation particle or a solid surface. In the event of an intermolecular collision, an appropriate molecular collision model is employed to compute post-collision velocities, and in the event of gas-surface collisions, a suitable GSI model is adopted to calculate the molecular velocity after reflection. In this work, the internal energy exchange is modeled using the Larsen-Borgnakke scheme. Further, the intermolecular collision is handled using the variable hard sphere model and the no time counter-collision sampling technique. The simulation is always evaluated as an unsteady flow, and a steady result is obtained as the large-time state of unsteady simulation. After achieving a steady flow, the simulation particles in each cell are sampled for a sufficient duration to decrease statistical scattering. All macroscopic field quantities (such as mass density, velocity, and temperature) and surface quantities (such as surface pressure, shear stress, and heat flux) are calculated based on these time-averaged data. [Results] Numerical results show that the distributions of gas pressure and mass flux are considerably affected by the GSI models. The lower the GSI accommodation coefficient, the higher the gas pressure and the larger the mass flux. Consequently, the GSI accommodation coefficients play a vital role in the compression factor and collection efficiency of the inlet. Furthermore, the decrease in the GSI accommodation coefficient from 1.0 to 0.2 leads to an increase in the compression factor and collection efficiency by a factor of 7 and 4, respectively. In addition, as the GSI accommodation coefficient decreases, the high-pressure region moves toward the ionization section, facilitating the ionization of neutral gas molecules. The following mechanism underlies this effect: after reflecting in a specular manner from the concave surface, the gas molecules congregate at the focus and enter the ionization section. [Conclusions] To improve the inlet design of an ABEP system, a combination of the geometric design and surface-material design should be adopted. A concave compression section should be employed, and at the same time, the inlet surface should be smoothened to decrease the GSI accommodation coefficient.

[Objective] Emergency relief supplies are crucial for dealing with disasters, and their reasonable and timely distribution relates to people's health and safety. Emergency relief supplies at rescue centers are limited and cannot meet the emergency needs of all affected areas simultaneously. Post-disaster emergency relief supplies face double challenges in this regard due to short supplies and limited transportation capability, resulting in the needs for medical rescue and materials of a disaster area in a short period. To develop a scientific and efficient post-disaster emergency response, we studied the constrained vehicle routing of emergency relief supplies based on demand urgency. Restrictions in traditional path planning, such as single objective, single depot, single distribution, undifferentiated supply, and closed scheduling, were considered.[Methods] The analytic hierarchical process was applied to measure the demand urgency index from personnel, facilities, and disaster resistance, considering the overall efficiency and key disposal. Furthermore, this study had multiple objectives, including the following: minimization of deprivation cost and response time, and maximization of demand satisfaction rate in the emergency rescue process. A constrained model of emergency vehicle routing was constructed, and a two-stage genetic algorithm was designed to deal with comprehensive distribution conditions, such as open scheduling, soft time windows, and demand splitting. The effectiveness and feasibility of the model and algorithm were verified using examples.[Results] The results revealed that the model effectively coped with the material distribution problem resulting from scarce transportation capacity and various degrees of disaster. The splitting strategy and open scheduling of vehicles guaranteed multiple services at disaster sites and optimal route combination. Moreover, relief progress in disaster sites (splitting demand, batch distribution, and service time) and vehicle dispatch schedules (distribution order, work duration, and resupply depot) were generated. During the planning period, the system loss was reduced by 40.3 %, and a 99.4 % material demand was obtained. When disaster derivation caused changes in road conditions, fluctuation parameters were inputted into the model. The model and algorithm adjusted the scheme with a low risk of service failure, and the adjusted scheme reduced the demand and supply by 1.5 % in the decision period.[Conclusions] Constrained route planning is implemented for flexible distribution conditions, such as demand splitting, soft time windows, and open scheduling, based on the dynamic change characteristics of demand and supply during sudden natural disasters. This study considers the demand urgency of key disaster areas and the efficiency of global relief to accommodate unexpected road events and maximize resource availability. With the circulation of distribution vehicles, the needs of disaster sites are gradually met within the decision-making cycle, which provides full play to the time utility of emergency relief supplies and transportation resources. The proposed model can form scientific and reasonable material distribution and vehicle scheduling schemes and evaluate the workload of each rescue center and vehicle to deploy work in advance, providing a theoretical basis and a decision-making reference for vehicle route planning of emergency relief supplies.

The frequent occurrence of major natural disasters not only endangers national stability and people's safety but also causes serious economic losses. Since most sudden natural disasters are unpredictable, how to transport emergency supplies to disaster-affected areas quickly and accurately has attracted wide attention. Unlike existing research, this study begins with the rescue characteristics of major natural disasters. In this study, an intelligent dispatching model of emergency supplies for multidisaster areas is constructed considering. Considering that the emergency materials of each rescue area to meet the needs of each disaster area, this study constructs an uncertain multiobjective intelligent dispatching model of emergency supplies in fully. Due to the uncertainty and fuzziness of information in emergency situations, using triangular fuzzy number method can help decision-makers to make effective decisions. Therefore, triangular fuzzy number method is used to express the uncertainty of emergency supplies demand and transportation time in different disaster areas. The rainstorm disaster in Henan Province, China, in 2021 is taken as a typical case in this study. The objective and actual data of emergency supplies dispatched in this disaster are obtained from the official websites of Zhengzhou Temporary Disaster Relief Reserve, Red Cross Society of China Henan Branch, and Henan Charity Network. This study sets emergency supplies as variable x(Z_e)_ij, unit cost as variable c_ij, transportation time as a variable t_ij. According to the triangular fuzzy number of emergency supplies demand and transportation time which set in this study, the uncertain variables are represented by the triangular fuzzy number method. Thus, the model is transformed into a deterministic multiobjective intelligent dispatching model. Two-dimensional Euclidean distance weighting is used to simulate the calculation and solve the model. Then, the linear interactive and general optimizer (LINGO) software is used to calculate the emergency supplies dispatching strategy from each rescue area to each disaster area. Given the actual situation of limited transportation conditions, each rescue area is usually unable to dispatch all emergency supplies at one time. Therefore, the weight of various emergency supplies is determined according to the urgency of the actual situation, and the LINGO software is used again in this study to calculate the phased emergency supplies transportation scheme. Finally, the optimal emergency dispatching strategy is formulated to meet the research objective in this study. Based on the above, a visual comparison is made between the results obtained using the constructed emergency supplies intelligent dispatching model and the demand quantity of emergency supplies in each disaster area. It can be seen that the dispatching quantity of various emergency supplies obtained by the model in this work has little difference from the actual emergency supply demand of each disaster area. As a result, large waste in major natural disasters can be avoided. The research findings show that the model has high reliability, and the simulation results are close to the actual situation. It can meet the emergency supplies demand of multidisaster areas and help decision-makers develop effective disaster relief strategies in major natural disasters.

[Objective] Most accidents in the construction industry are caused by hazards that remain unrecognized due to inexperience and inattentiveness. Novice workers have difficulty learning how to quickly and accurately determine the source of a hazard and avoid it; thus, it is necessary to develop a dynamic hazard identification process-assisted education pattern. Eye-movement modeling examples (EMMEs) are videos of gaze replays of hazard identification trajectory by an expert with a verbal explanation. [Methods] This study constructed the EMMEs of hazard identification by an expert to explore the mechanism of its influence on workers' safety education at different experience levels. We created eight virtual construction sites for hazard identification testing, which mainly included falls, collapses, electric shocks, lacerations, explosions, and unsafe actions. A participant's task was to search for hazards, i.e., to visually inspect construction site scenarios and determine where a safety accident might occur. An eye tracker was used to collect the search patterns of experienced and novice workers before and after EMME training. Eye movement data were collected from 14 novice workers and 10 experienced workers. The study followed a 2? mixed-group design with between-subject factor experience (experienced vs. novice workers) and a within-subject factor case (before vs. after EMME training). Hazard identification accuracy, task completion time, and sequence standardization were used as indicators to measure the identification performance of the participants before and after EMME intervention. [Results] Herein, a t-test was used to evaluate the difference between the hazard identification performances of novice and experienced workers, and the interaction effect was used to test the moderating effect of EMMEs on prior experience and hazard identification performance. The main results were as follows:(1) Participants with EMME intervention performed better at hazard identification and showed higher hazard identification accuracy, shorter task completion time, and higher sequence standardization after EMME training. This finding confirmed that instructions comprising EMMEs effectively improved construction safety education. (2) The hazard identification performance of experienced workers was better than that of novice workers in the pretest; compared to novice workers, experienced workers identified more hazards in less time with more standard sequences before EMME training. The experienced workers consistently inspected laborers first, then the equipment or environment, and finally, the entrance. Novice workers typically inspected the hazards in the same order but with a less consistent scan path. (3) The EMME-based safety education mode had the expertise reversal effect. Participants with rich work experience showed insignificant improvement in performance after EMME training, while novice workers benefited far more from EMME intervention than experienced workers. [Conclusions] Our results demonstrate the potential of EMMEs to indirectly teach strategic hazard identification sequences and contribute to deeper safety education, particularly for workers with limited work experience. This study has educational importance as it provides new evidence of the potential of eye-tracking technology as an indirect instruction tool.

The group analytic hierarchy process (AHP) was used with boxplots and Spearman's rank correlation coefficient analyses. The relevant parameters of the hierarchy of decisions were calculated with Python. This multi-criteria decision-making model was then built. Previous investigations have not been reliable and the basic AHP is not always consistent. This Group AHP was then used to compare various vibro-stone column packing methods for treating the deep overburden dam foundation of a hydropower station in southwest China. The results show that the various project participants have different preferred technical routes. Designers and researchers are more inclined to choose innovative technical methods; while owners, constructors and supervisors are more inclined to use mature, reliable schemes. An intelligent feed device and a method were developed, which improve the quantity accuracy and the quality of the vibro-stone column filler for the deep overburden dam foundation.

[Objective] Suppression firing is a crucial approach to control the spread of forest fires. However, existing suppression firing mainly relies on rare quantitative analysis by experts, making efficient forest fire control efforts difficult to perform.[Methods] In this paper, a fire spread prediction model was implemented to quantitatively simulate and analyze suppression firing. This model adopted the cellular automata algorithm to define the fire spread as a grid dynamics problem. The forest landscape was divided into contiguous regular cells with different cell burning states (S₀: unburned; S₁: ignited; S₂: flashover; S₃: extinguishing; S₄: extinguished). Then, multimodal environmental factors such as fuel type, slope, wind, and temperature were considered to construct the rate of the spread function and predict the fire spread speed in various complex scenarios. Next, state update rules were proposed to define how the burning state of forest cells was transformed for different fire conditions. The minimum travel time method was then adopted to iteratively calculate the ignition time of each cell in the forest landscape. Therefore, the spatiotemporal evolution of forest fires in complex environmental scenarios was quantitatively modeled. Additionally, a trigger mechanism was proposed to define reverse ignition behavior as a grid cell with specific time-trigger constraints. This mechanism realized a quantitative simulation analysis of human ignition factors with different spatiotemporal conditions.[Results] To verify the reliability and feasibility of our model, a real forest fire that occurred in the Beibei District of Chongqing in August, 2022 was chosen as the study case. Fire data (fuel type, slope, historical weather, fire perimeter, etc.) and firefighting records (the location and time of fire ignition, suppression firing description, etc.) were collected to reconstruct the firing process. Our model was applied to the suppression firing in this forest fire to analyze the fire control effect for different environmental conditions. The experimental results showed that our model was superior in predicting the spatiotemporal spread of forest fire with competitive model performance (Jaccard: 0.732; Sorensen: 0.845). The spatial location and ignition time of the reverse ignition in suppression firing were quantitatively analyzed and visualized, demonstrating how the reverse fire burned the fuel in advance and impeded the spread of free fires.[Conclusions] Quantitatively modeling the suppression firing can provide effective decision-making for wildfire firefighters to formulate accurate fire control strategies and improve the modernization capability of forest fire management. As a highly complex, dangerous firefighting strategy, more research on the combustion mechanism and simulation method of suppression firing is needed, such as the formation mechanism and modeling method of local microclimate in a forest fire landscape, the barrier effect of the isolation zone, and spatial optimization.

An equivalent pore network model (EPNM) describes complex pore structures in a porous media by statistical parameters. Previous studies using such models have focused on seepage and mechanical dispersion, with few studies considering the effect of molecular diffusion on solute transport. In this study, the convection, molecular diffusion and mechanical dispersion of solutes in porous media were studied using an EPNM to predict the solute transport in porous media. A sensitivity analysis of the model parameters was used to study the effect of the pore structure characteristics on the effective diffusion coefficient of the porous media. The influence of molecular diffusion on the hydrodynamic dispersion was analyzed by comparing numerical results with and without molecular diffusion. The results show that the effective diffusion coefficient, which negatively correlates with the throat curvature and positively correlates with the coordinate number and the connection number ratio, is affected by both the pore volume and the pore-throat diffusion capacity. The molecular diffusion correlates with the convection-induced mechanical dispersion to accelerate the solute transport in the low-velocity region. The results of this study show the microscopic mechanisms influencing molecular diffusion for hydrodynamic dispersion as a theoretical basis for predicting the solute transport flux in pore network models.

[Objective] Ontology structure has been proved to be particularly important in the construction and organization of a knowledge graph (KG). A comprehensive method for the modeling, updating, and application of KG with the guidance of domain ontology needs to be explored. In view of the common knowledge gap in engineering safety management, this paper aims to propose an ontology-based framework to achieve domain knowledge modeling and updating. Using the highway engineering field as an example, this paper demonstrates how safety knowledge can be automatically extracted from industry-standard text data to facilitate the construction of a domain KG. Subsequently, the safety management scenarios are developed based on the building information model (BIM), and the auxiliary role of intelligent knowledge in safety management is demonstrated to verify the effectiveness of the engineering application of the developed KG. [Methods] This paper used the ontology-guided domain knowledge extraction method to construct the domain KG and proposed a knowledge network-guided method to update the ontology. Specifically, a layered knowledge system with multiple dimensions was summarized as the ontology layer based on the management approach and the established standard specifications within highway engineering. Following the guidance of the ontology layer, a structured knowledge network acting as the data layer was extracted from massive text materials by developing a series of knowledge extraction procedures. Consequently, a knowledge-flowing method from the data layer to the ontology layer was proposed. Three categories of methods based on the essence and composition of entities and the clustering of the entity's core words were summarized to realize the automatic updating of the ontology layer. Finally, combined with the developed highway safety information retrieval and application system, this paper demonstrated the organization and application of the constructed domain KG, thus verifying the effect of introducing ontology in the organization and deployment of knowledge. [Results] The developed ontology of highway engineering safety knowledge was featured as a layered knowledge system with seven levels and 390 nodes connected with~300 000 valid entity nodes in the data layer, facilitating the creation and integration of the KG's logical structures. The proposed method for updating the domain ontology aided by over 1 000 technical terms was demonstrated to be effective, with an increment of 51.5% in the expansion of the nodes to the ontology. The designed method of linking the ontology-guided domain KG with the BIM was validated for its feasibility through practical implementation within a real highway engineering safety management system, displaying the positive impact of ontology's guidance in the organization and expansion of knowledge. [Conclusions] This paper concentrates on the domain of highway engineering safety and presents a comprehensive paradigm for constructing, updating, and applying a domain KG to demonstrate methodological innovation in ontology updating. The results extend the application scope and technical approaches of KG technology, thereby enhancing information technology level in engineering safety management. Moreover, the findings of this research can be used for BIM evaluation and safety guidance in highway engineering construction projects, thereby advancing the level of information technology in construction safety management.

[Significance] Combustion instability is a crucial issue in developing low-emission gas turbine combustors. Meanwhile, future combustors will possess higher temperatures, wider operation parameter ranges, and more complicated geometric structures (e.g., axially staged and annular). Thus, combustion instabilities have the features of high amplitude levels, multiple and time-varying frequencies, and the coexistence of several modes. Passive control employing acoustic dampers for attenuating oscillations has many advantages, such as simple structures, high reliabilities, and low costs. However, the present damper designs encounter great challenges for future combustors. Therefore, multimode wide-absorption acoustic dampers and systematic design optimization methods for multiple dampers must be investigated. [Progress] This paper briefly reviewed the research progress of mechanisms and optimization methods for acoustic dampers and the recent corresponding work conducted by the authors. First, the mechanisms for conventional and multi-bandwidth acoustic dampers were analyzed. Previous acoustic models for holes assumed that the thickness is ignorable and two open ends are inserted into semi-infinite space. A novel semianalytic acoustic model for short holes was proposed to consider sound-vortex interactions in detail. Sound generation and absorption can be well predicted by this model. Additionally, the performance of holes was sensitive to the shape of the hole edges. To broaden the absorption bandwidth of the Helmholtz resonators, parallel perforated materials were installed at the neck of the resonators. A theoretical model was derived to calculate the sound absorption coefficient of this type of resonator and effectively captured the nonlinear effect at the neck. Traditional resonators only possess a single frequency band for suppressing instabilities. Two multi-bandwidth resonators based on elastic membranes and multiple cavities were proposed by the authors. The results showed that elastic membranes and multiple cavities may introduce new frequency bands. Meanwhile, a low-order network model coupled with nonlinear flame dynamics and the acoustic models of resonators was developed to successfully predict thermoacoustic instabilities in cylindrical and annular combustors. The stability of annular combustors could be affected by the asymmetrical flame responses after introducing acoustic resonators. Subsequently, we examined the effects of complex thermoacoustic parameters on the acoustic characteristics of resonators and optimization strategies for designing multiple resonators. A theoretical model combined with the energy equation was established to explore the effect of a temperature difference on resonator performances. The results showed that the entropy disturbance caused by large temperature differences could affect the thermoacoustic stabilities of combustors. The cross-section of resonators was another critical factor in influencing the resonator properties. The acoustic characteristics of perforated liners with variable cross sections were theoretically and experimentally explored. Decreasing the cross-section increased the range of absorption frequency bands. The introduction of resonators for suppressing thermoacoustic instabilities changes the acoustic modes of combustors and the intrinsic modes of flames. An available strategy considering these influences was determined for reasonably designing the resonators. There are many adjustable parameters when multiple resonators are employed simultaneously. An efficient multiparameter adjoint-based optimization strategy for multiple resonators was developed. This algorithm is based on treating the low-order network model by performing the adjoint method. [Conclusions and Prospects] The next generation of multimode wide-absorption acoustic resonators urgently needs to be explored. Moreover, the effects and mechanisms of nonlinearity, mean flow, temperature difference, and other complex physical parameters on the properties of acoustic resonators need to be further explored. Meanwhile, the effectiveness and robustness of current optimization strategies for designing multiple resonators must be improved.

[Objective] The ridership characteristics of urban rail transit stations are closely related to the surrounding built environment and socio-economic factors, and the influence of different influencing factors on ridership characteristics also has temporal and spatial heterogeneity. Considering the complexity of influencing factors on station ridership, this paper uses the multiscale geographical weighted regression (MGWR) model to analyze the influencing factors of ridership at rail transit stations in different temporal scales.[Methods] This paper selects the station ridership on weekdays as the dependent variable, which is divided into five categories, including the average daily ridership, inbound ridership of morning peak hours, outbound ridership of morning peak hours, inbound ridership of evening peak hours, and outbound ridership of evening peak hours. A total of 23 independent variables are selected from three aspects: station attributes, connectivity, and the built environment. The variance inflation factor and Moran index are utilized to test the linear correlation and spatial autocorrelation between independent variables, respectively. The MGWR model is applied to construct the analysis model of ridership characteristics, and three indicators, including the residual sum of squares (RSS), adjusted R², and the corrected Akaike information criterion (AICc), are employed to compare the performance of the ordinary least squares (OLS), geographically weighted regression (GWR), and MGWR models. The influencing factors and their interaction with rail transit station ridership in different temporal scales are developed. Finally, this method is applied to analyze the influence degree of ridership characteristics at Nanjing rail transit station.[Results] The following results are presented. 1) The MGWR model is more reliable than the OLS and GWR models. 2) The average daily ridership analysis model, which ignores the impact of morning and evening peak hour ridership, has the most significant independent variables. 3) The distance to the city center has a significant negative impact on station ridership, indicating that the agglomeration of station ridership is evident when the station is close to the city center. 4) The stations with a high proportion of residential and living facilities have a strong attraction to the morning peak inbound and evening peak outbound ridership, whereas those with a low proportion of residential and livings facilities have a strong attraction to the morning peak outbound and evening peak inbound ridership. Three significant local variables, namely tourism facility POI density, enterprise and office POI density, and the ratio of floor area on commercial lands to the total floor area, are available, and these local variables have different impacts on rail transit ridership at different temporal scales. Tourism facility POI density has negative spatially varying impacts on the average daily ridership, inbound ridership of morning peak hours, and outbound ridership of evening peak hours. Enterprise and office POI density has a negative spatially varying impact on inbound ridership of morning peak hours but has a positive spatially varying impact on outbound ridership of morning peak hours. The ratio of floor area on commercial lands to the total floor area has positive and negative spatially varying impacts on inbound ridership during evening peak hours. This finding implies that not all the commercial buildings around the rail transit stations are attractive to the inbound ridership during evening peak hours.[Conclusions] The MGWR model considering spatial autocorrelation can capture numerous influence scales of different variables and reduce the deviation of results. The developed method in this paper achieves the expected goal and depicts the interdependence between ridership and influencing factors from the station level.

[Objective] As a significant research branch in the field of data mining, missing value imputation (MVI) aims to provide high-quality data support for the training of machine learning algorithms. However, MVI results for large-scale data sets are not ideal in terms of restoring data distribution and improving data prognosis accuracy. To improve the performance of the existing MVI algorithms, we propose a distribution consistency-based MVI (DC-MVI) algorithm that attempts to restore the original data structure by imputing the missing values for large-scale data sets.[Methods] First, the DC-MVI algorithm developed an objective function to determine the optimal imputation values based on the principle of probability distribution consistency. Second, the data set is preprocessed by random initialization of missing values and normalization, and a feasible missing value update rule is derived to obtain the imputation values with the closest variance and the greatest consistency with the complete original values. Next, in a distributed environment, the large-scale data set is divided into multiple groups of random sample partition (RSP) data blocks with the same distribution as the entire data set by taking into account the statistical properties of the large-scale data set. Finally, the DC-MVI algorithm is trained in parallel to obtain the imputation value corresponding to the missing value of the large-scale data set and preserve distribution consistency with the non-missing values. The rationality experiments verify the convergence of the objective function and the contribution of DC-MVI to distribution consistency. In addition, the effectiveness experiments assess the performance of DC-MVI and eight other MVI algorithms (mean, KNN, MICE, RF, EM, SOFT, GAIN, and MIDA) through the following three indicators:distribution consistency, time complexity, and classification accuracy.[Results] The experimental results on seven selected large-scale data sets showed that:1) The objective function of the DC-MVI method was effective, and the missing value update rule was feasible, allowing the imputation values to remain stable throughout the adjustment process; 2) the DC-MVI algorithm obtained the smallest maximum mean discrepancy and Jensen-Shannon divergence on all data sets, showing that the proposed method had a more consistent probability distribution with the complete original values under the given significance level; 3) the running time of the DC-MVI algorithm tended to be stable in the time comparison experiment, whereas the running time of other state-of-the-art MVI methods increased linearly with data volume; 4) the DC-MVI approach could produce imputation values that were more consistent with the original data set compared to existing methods, which was beneficial for subsequent data mining analysis.[Conclusions] Considering the peculiarities and limitations of missing large-scale data, this paper incorporates RSP into the imputation algorithm and derives the update rules of imputation values to restore the data distribution and further confirm the effectiveness and practical performance of DC-MVI in the large-scale data set imputation, such as preserving distribution consistency and increasing imputation quality. The method proposes in this paper achieves the desired result and represents a viable solution to the problem of large-scale data imputation.

[Objective] Lunar and Mars exploration projects face the issue of autonomous spacecraft landing or taking off on the surface of the target celestial body in a low-gravity environment. Several mechanical problems arise when a spacecraft is flying in a low-gravity environment, which is different from Earth's gravity environment. To solve these problems, it is necessary to verify the key actions of spacecraft for soft landing on or taking off from the target celestial body.[Methods] Since the Chang'e-3 mission of the second stage of lunar exploration, the test system of the suspension low-gravity simulation technology has been studied via fast follow-up and multilevel compensation, and the real-time tracking technology for the spacecraft motion in large space has been developed to keep the pulling force applied in the entire process constant and the deflection angle of the force direction relative to the vertical direction sufficiently small. Through the technical improvement of the third stage of the lunar exploration mission and the technical upgrade iteration of the Mars exploration, a complete set of technical systems for the spacecraft has been successfully constructed to simulate the low-gravity landing and take-off test of extraterrestrial celestial bodies on the earth. A three-dimensional (3D) follow-up system adopts the two-level linkage driving technology of a large-scale follow-up and rapid and accurate tracking to construct a landing and take-off test method for simulating the low-gravity environment of a spacecraft on the ground, thus overcoming a series of technical difficulties, such as large test space and high control accuracy, and employing several key technologies, including multi degree-of-freedom linkage of the 3D follow-up system and high-speed and high-precision coordinated control of the large-inertia electromechanical equipment.[Results] The large-scale follow-up tracking of the spacecraft in the test process was achieved by controlling the movement of the rapid follow-up platform through the parallel-link system driving technology, and the requirement of the absolute inclination angle of the lifting rope was realized by applying a high-precision tension control to the spacecraft through the rapid follow-up platform device and following the movement of the spacecraft in the horizontal direction. Additionally, the horizontal stiffness of the fast follow-up platform was improved to overcome the adverse effects of the coupling shaking of the two-level linkage equipment in the spacecraft test.[Conclusions] The system has been successfully applied to a series of real ground test conditions, such as hovering, obstacle avoidance, slow descent, landing, and take-off of China's Chang'e-3 and Chang'e-5 in the lunar exploration project and Tianwen-1 spacecraft in Mars exploration. The test data which can support the research and engineering exploration of spacecraft are obtained, providing a key technical means for verifying and optimizing the comprehensive performance parameters of the spacecraft. With the continuous development of space missions, the mechanical environment simulation and ground test technology regarding spacecraft landing and take-off from extraterrestrial bodies pose new challenges. The 3D follow-up system for a low-gravity simulation will further develop toward a high-precision, large-load, and high-dynamic simulation technology, laying the foundation for the application of ground low-gravity simulation tests for manned lunar landing and deep space exploration missions.

[Significance] Neither a global atmosphere nor a magnetic field exists above the lunar surface. The lunar surface is exposed to high-energy ultraviolet radiation and solar wind, which charge a large amount of lunar dust to form high-potential, local electric fields. The lunar mountains, with a length of more than ten kilometers and a vertical height of several kilometers, block ultraviolet radiation from the sun, creating a whole light-dark junction region with a shadow region on the lunar surface. Meanwhile, the occlusion of the lunar surface by a detector or a rover also forms a local light/dark junction region under sunlight. Under the lunar environment, complex electric fields exist at the whole and local light-dark junction regions, which leads to the abnormal phenomenon of charged lunar dust transport. In this paper, the whole and local light-dark interface models were proposed, and the particle-in-cell method and leap-frog method were used to study the lunar dust transport anomalies of the two models based on measured data of the Apollo lunar dust samples. The results showed that a very significant abnormal phenomenon of lunar dust transport occurred in the whole and local light-dark interface models. First, the lunar dust transport path was bell-shaped or parabolic, and a large amount of lunar dust accumulated above the boundary in the whole light-dark interface model. Moreover, the lunar dust transport phenomenon had an obvious horizontal transport characteristic, and the horizontal transport velocity was approximately two to ten times that of the vertical direction. Particularly, the abnormal phenomenon of lunar dust transport at the junction between light and dark was more severe and more likely to occur in the whole light-dark interface model. Second, in the local light/dark interface model, significant anomalies of lunar dust transport were found on both the left and right side of the detector, where a large amount of lunar dust was transported bidirectionally from one side to another side, passing through the detector in the horizontal direction. In particular, a large or small lunar dust vortex rotated around both sides of the left and right detector, resulting in a local "moondust storm" around the detector with a number density of approximately 1.4×10⁵ particles per cubic meter. This paper predicts the abnormal phenomenon of lunar dust transport for the whole light-dark junction region caused by mountain occlusion, which can indirectly verify the observed occurrence of the "horizontal glow" phenomenon. Abnormal transport of lunar dust in the local light-dark junction region may be one of the main reasons for the deposition of much lunar dust on the detector/rover and so on. The abnormal phenomenon of lunar dust transport is not only potentially harmful to the current lunar detector/rover and so on, but also a key problem that human exploration activities cannot avoid. The results of this study have not only an important reference value for selecting the landing site of a lunar detector and the traveling route of a rover but also helpful to reduce the lunar dust pollution caused by the detector/rover and so on.

[Objective] Leakage accidents in urban gas pipeline networks occur from time to time, and most of them are accompanied by secondary disasters, such as explosions, fires, and building collapses, which seriously threaten the safety of people's lives and property. Previous research on gas accident rescue capability primarily focuses on gas enterprises or indoor gas emergencies, and research on accidents associated with gas pipeline networks is lacking. Some studies have limitations, such as broad evaluation indicators, vague content, and limited scope of assessment objects, which cause difficulties in applying the evaluation system in practice. This study aims to identify the weaknesses in the emergency rescue process for accidents associated with urban gas pipeline networks, effectively assess the emergency rescue capabilities for such accidents, and help improve the emergency rescue efficiency and gas safety guarantee level. [Methods] Herein, the emergency rescue characteristics for accidents associated with urban gas pipeline networks were analyzed and summarized, and the rescue capabilities for these accidents were evaluated. First, based on an in-depth analysis of emergency plans and accident cases associated with gas pipeline networks, the emergency rescue elements of accidents were extracted and sorted. Furthermore, the emergency rescue process was constructed. By summarizing the limitations in emergency rescue, an indicator system comprehensively reflecting emergency rescue capabilities was established based on four aspects, namely humans, pipelines, materials, and management. The system included 4 first-level indicators, 12 second-level indicators, and 27 third-level indicators. Second, the subjective-objective combination weighting method of the analytic hierarchy process (AHP) and the criteria importance through intercriteria correlation (CRITIC) method were used to calculate the weight of each indicator to reduce the possibility of excessive subjectivity caused by expert scoring to a certain extent. Combining the weight of each indicator can help identify and focus on the indicators with a high degree of importance. Finally, an emergency rescue capability evaluation model was established using the fuzzy comprehensive evaluation approach to realize the quantitative evaluation of the emergency rescue capabilities for accidents associated with gas pipeline networks in specific regions. The model was applied to Zhangwan District, Shiyan City, Hubei Province. [Results] The results show that indicators such as the “supply-demand ratio of rescue personnel”, “effectiveness of information transmission”, and “formulation and revision of emergency plans” account for a relatively large weight compared to other indicators. The indicators of “cooperation and coordination ability of rescuers”, “equipment performance”, and “emergency drill effect” are the weak links in the emergency rescue process of accidents associated with the gas pipeline networks in the region. Therefore, the departmental interaction needs to be strengthened, the construction of the rescue coordination mechanism needs to be improved, and joint prevention and control and coordinated rescue capabilities need to be enhanced. Furthermore, to standardize emergency drill training, the safety production investment guarantee for local gas companies should be increased, and to improve the design and planning of training content, online and offline integrated learning is necessary. [Conclusions] The feasibility and applicability of the evaluation system were verified through the application case. This evaluation system for the emergency rescue capability of accidents associated with urban gas pipeline networks offers a theoretical basis and feasible approach for establishing, improving, and evaluating emergency measures for accidents associated with urban gas pipeline networks.

[Significance] Climate change is the primary challenge that intensely affects sustainable human development. The transport sector has been one of the major sources of carbon emissions and is considerably affected by climate change. Because of the growth of China's economy and total transport demand, transport-related carbon emissions are also gradually increasing. Moreover, frequent complex and extreme climate events with clear regional differences have negatively affected the construction, maintenance, and operation of the transport infrastructure. Therefore, China's transport sector needs to reduce carbon emissions for green and low-carbon developments and improve its adaptability and resistance to various adverse climatic conditions. However, China's transport sector still faces many challenges in mitigating and adapting to climate change, and its policy tools, measures, and basic capacity to cope with climate change need to be enhanced. Therefore, transport sector-related strategies and routes to adapt to climate change need to be explored. [Progress] First, the policies and measures implemented in different countries to address climate change were introduced from the perspectives of mitigation and adaptation. Second, the advancements made by China's transport sector in mitigating climate change were summarized from the perspectives of the construction of green and low-carbon transport infrastructure, optimization of the transport structures, and promotions and applications of new and clean energy. The measures implemented to adapt to climate change in China's transport sector were summarized from the perspectives of improving the adaptability of the transport infrastructure, strengthening the monitoring and warning systems of climate change, and managing risk. Third, the interactions between each subfield and sublink of the transport system and climate change, as well as the main measures implemented to mitigate and adapt to climate change in the transport sector, were analyzed. Finally, key areas, strategies, and methods to mitigate and adapt to climate change were proposed. [Conclusions and Prospects] Analysis results are provided and discussed. First, the current plan for China's transport response to climate change needs improvement. The capacity to respond to climate change has not been planned at the subfield and sublink level of the transport system. For mitigating climate change, carbon emissions reduction measures, such as the promotion of new energy vehicles and ships, as well as the optimization of the transport structure, are inadequate. Furthermore, the assessment of the effects of the transport infrastructure on climate change is still in its infancy. Second, the direction of the transport system's development should be combined with the strategic requirements of mitigation and adaptation to climate change. Third, in the transport field, the infrastructure, equipment, and transport structure should be improved; moreover, the infrastructure should be adapted to climate change, and emergency support of transport equipment and transportation organization in extreme weather should be optimized to enhance the capability to adapt to climate change. Finally, the following measures are proposed: Mitigation and adaptation to climate change should be jointly and appropriately implemented to comprehensively address climate change in the transport sector. Greenhouse gases and air pollutants should be jointly controlled to realize the goal of “double carbon”. Adaptation to climate change should be applied in conjunction with ecological protection and restoration to strengthen the capacity of the transport sector to adapt to climate change.

[Objective] Future community is a novel type of ecological low-carbon urban functional unit that follows sustainable development objectives and the sponge city construction concept. Some studies have employed different methods targeting data accessibility and technical requirements to explore future community planning. However, a systematic method is still lacking for different planning and design stages, additions to which will support the planning layout of sponge source facilities for future communities.[Methods] To integrate the future community planning methods incorporating the sponge city construction concept, a multimethod framework for the sponge source facility layout of the future community was constructed, adopting the volume capture ratio (VCR) method, the modeling method, and the multiobjective optimization method for different data and technical requirements. The results from the case study of a community to be transformed into a future community in a rainy southern Chinese city showed that the VCR method demonstrated the lowest data and technical requirements, which could generate a layout scheme meeting the volume capture ratio of annual rainfall (VCRAR). This method is particularly suitable for the early stages of the sponge source facility layout planning for limited data. However, a model was required for further assessments of pollution and carbon reduction, along with additional relevant data (drainage network, rainfall data, etc.). To achieve multiobjective comprehensive environmental benefits and the cost-effectiveness of future communities, a multiobjective optimization method could be incorporated. Nevertheless, intelligent optimization algorithms and model coupling technology were indispensable to achieve multiobjective optimization.[Results] The runoff management efficiencies of different schemes employed by these methods indicated that the sponge source facility layout scheme by the VCR method achieved approximately 80% VCRAR. The VCR-based scheme was further evaluated by the Storm Water Management Model (SWMM), demonstrating a decline in the runoff peak flow from 5.65 m³·s^-1 in the traditional scheme (without sponge facilities) to 2.17 m³·s^-1, and the VCRAR changed from 51.87% in the traditional scheme to 79.43%. A 21.69%—30.52% reduction in the peak concentrations of total suspended solids, nitrogen, phosphorus, and chemical oxygen demand and a 284.87 t·y^-1 carbon reduction over the traditional scheme were recorded, exhibiting significant pollution and carbon reduction improvement of the VCR-based scheme. The multiobjective optimization scheme based on the multiobjective optimization method by coupling SWMM and NSGA-II aimed for the best cost-effectiveness, which resulted in a 3.29% and a 1.51% decrease in the green roof and the sunken greenbelt area, respectively, and a 2.13% increase in the permeable pavement area, as well as an 18.67% reduction in the cost compared to the VCR-based scheme. Thus, the increased area of permeable pavement made it the preferred choice. Moreover, the multiobjective optimization scheme displayed superior peak flow reduction (21.20% decrease), peak concentration reduction of different pollutants (6.32%-16.67% decrease), rainwater reuse rate (1.17%-2.65% increase), and carbon reduction (7.91%-12.66% increase) over the VCR-based scheme. However, in the multiobjective optimization scheme, the increase in the permeable pavement area increased the carbon emission by 178.40 t as compared to the VCR-based scheme.[Conclusions] Utilizing the carbon emission indicator as a control objective in the optimization process is necessary for future studies. Nonetheless, the multiobjective optimization scheme achieved higher net carbon reduction benefits due to higher annual reductions and needed about seven years to achieve carbon emission recovery. Briefly, the VCR method has a simple and easy operation, and it can meet the requirements of future community planning and runoff control objectives, while the multiobjective optimization method can achieve the best environmental benefits and cost-effectiveness.

Start-up transients in mixed-flow pumps are very complex due to the flow variations and rotational stall during start-up. A transient head equation was solved with a pipe resistance equation in this study to give a theoretical model for the varying flow rate and head during start-up of a mixed-flow pump. The model included the rotational acceleration to predict the variation of the flowrate and head during start-up. The start-up was also modeled with a three-dimensional numerical model of the mixed-flow pump and pipe system to predict the transient pump characteristics. The model predictions agree well with the numerical results to validate the theoretical model. During start-up, the flowrate does not increase as fast as the speed but continues to slowly increase after the pump has reached the maximum rotational speed. The transient pump head can be divided into the steady-state head, the acceleration head and the inertia head with the acceleration and inertia heads greatly influencing start-up.

[Objective] The pipe section collection time is typically based on the theory of steady full pipe uniform flow when using the reasoning formula method to calculate the design flow of a storm pipe network, but the actual water flow in the storm pipe is non-steady, causing errors in the calculation of the design flow that, when applied to a larger scale pipe network, gradually reduce the calculation accuracy. In this context, the paper suggests a design flow computation method for storm pipe networks based on kinematic wave simulation. [Methods] In this paper, the design flow of pipe sections is solved using kinematic waves under the condition of ensuring the equivalent setup of model parameters and storm pipe network starting design parameters. This paper combines the Horton infiltration model and the φ index method to calculate infiltration intensity in the surface rainwater runoff stage. The runoff generation is calculated with the objective of achieving equivalence of the volumetric runoff coefficient and discharge runoff coefficient. Taking surface catchment time and linear confluence curve type as input, and coupling with the isochrones model, the equivalence setting of design conditions and stormwater outlet inflow process line calculation are completed. In the pipe section confluence process, the pipe section flow process line is calculated by inputting the corresponding stormwater inlet inflow process line into the node inflow mode and computing the pipe section confluence process using the stormwater management kinematic wave model. The stormwater inlet inflow process line of the designed pipe section and the upstream pipe section flow process line connected with it are superimposed to complete the calculation of the pipe section design flow process line. Combined with the hydraulic design of the stormwater pipe section, the whole storm pipe network design is realized based on the geospatial data abstraction library development technology process. [Results] The results of a storm pipe network example in a particular area (with a total size of 4.506 km²) showed that: (1) When compared to the reasoning formula method, the stormwater pipe section created using the kinematic wave simulation approach had a quick catchment time and a greater design flow rate. (2) The flow calculation difference between the two approaches increased over time as catchment time and catchment area increased, reaching a maximum increase of 39.45%. (3) Under the 10-year rainfall scenario, the design storm pipe network obtained by the two calculation methods of equivalent design conditions reduced the number of overflow nodes, total overflow volume, and length of pipe section overload by 8.57%, 28.57%, and 38.48%, respectively, compared to the reasoning formula method. [Conclusions] By comparing the differences in the design results obtained by the two calculation methods for different catchment times and catchment areas, it can be seen that for large projects, it is advisable to use the kinematic wave simulation method to calculate the design flow of the storm pipe network. In a simulated analysis with a 10-year exceedance of rainfall, the storm pipe network designed by the kinematic wave simulation method has better flood prevention performance.

[Objective] Hydrogen demands in refineries are increasing annually because of the growing processing of heavy crude oil, which necessitates optimizing the hydrogen network to improve hydrogen usage. The cost associated with hydrogen compressors is the second largest in a refinery hydrogen network, following the fresh hydrogen cost. Thus, the synthesis of hydrogen networks considering gas compression has been an active topic in process systems engineering. Previous work has been modeled on reciprocating compressors, focusing on reducing the number of compressors and/or compression power consumption. However, reciprocating and centrifugal compressors are widely used in refinery hydrogen networks. The advantage of centrifugal compressors is their suitability for large gas flow rates without too high exhaust pressures, while reciprocating compressors have high and stable exhaust pressures and are suitable for small gas flow rates.[Methods] This work presents a hydrogen network superstructure that considers the selection of multistage centrifugal and reciprocating compressors. Compressor selection is determined based on the characteristics of reciprocating and centrifugal compressors considering their inlet gas flow rates and exhaust pressures. A mixed integer nonlinear programming (MINLP) model is formulated to minimize the total annualized cost, comprising fresh hydrogen, compressor investment, and compression power. The developed MINLP model is examined based on a hydrogen network reported in the literature. It is coded in the general algebraic modeling system 35.2 and can be directly solved by the BARON solver.[Results] The results indicated that the optimal hydrogen network contained three centrifugal compressors and six reciprocating compressors, with one reciprocating compressor for two-stage compression and one for three-stage compression. The flow rates of the three centrifugal compressors were larger than the upper flow rate limit of the reciprocating compressors, while the outlet pressures were lower than the upper outlet pressure limit of the centrifugal compressors.[Conclusions] This phenomenon indicates that the flow rate constraint dominates the compressor selection in this hydrogen network. Since the cost correlation of the centrifugal compressor is smaller than that of the reciprocating compressor in this study, the centrifugal compressor is preferred when both types of compressors meet the compression demands. Hence, only hydrogen streams with small flow rates and large compression ratios are chosen for the reciprocating compressors. Compared with the previous work, although the numbers of compressors are identical, the optimal hydrogen network structures differ notably, and this study obtains small compression power consumption. This result is obtained because earlier studies neglected compressor selection, and the mathematical model in this study prefers the less expensive centrifugal compressor. Therefore, the flow rates of several hydrogen streams are enlarged to satisfy the flow rate constraint of centrifugal compressors, which is also more consistent with refinery practice. Finally, the computation time of the MINLP model is only 0.72 s, thereby demonstrating the usefulness and convenience of the proposed method.

[Objective] Tropical cyclone (TC) is one of the biggest threats to life and assets in coastal areas. TC is a stochastic event characterized by various hazards, such as strong wind, heavy rain, storm surge, and flooding, which can cause significant impacts individually or in combination. Exploring the relationship between the multiple attributes of TC can help estimate the severity of TC and aid in the emergency response and risk management. Strong wind and heavy rain are the two most severe hazards of TC disasters. Generally, TC weakens rapidly after landfall due to the mountainous terrains in coastal areas, and its intensity (wind) decays within a very short period. The maximum wind speed (MWS) of the TC at landfall reflects the threats posed by the strong winds of the cyclone. MWS also contributes to the rise in water levels caused by storm surges. Total precipitation (TP) can indicate the intensity of TC rainfall as well as the potential impact of inland floods and water logging. However, the relationship between MWS and TP is complex and nonlinear, and there is a lack of a clear formula to express this relationship. Copula is an effective probability method to model the dependence between two or more variables with uniform cumulative distribution functions (CDFs).[Methods] Therefore, in this study, a bivariate copula function was used to construct the joint probability of MWS and TP. Four marginal distribution models (Gamma, Gumbel, Weibull, and generalized extreme value (GEV)) were first fitted based on 553 MWSs at landfall and TPs over land in China (1951-2015). Three two-dimensional Archimedean copula functions (Clayton, Frank, and Gumbel) were then used to construct the joint probability of MWS and TP. The Kolmogorov-Smirov (K-S) test at a 5% significance level and the ordinary least squares (OLS) values were used to determine the best marginal and copula models. The characteristics of marginal CDFs and joint probability were also discussed. The conditional probability of TP was also calculated and discussed since TC intensity (wind) is easier to achieve than precipitation.[Results] The results of this study are as follows: (1) Weibull and Gamma are the best marginal CDFs for MWS and TP, respectively, and the Gumbel copula is the best copula function. Fitted Gumbel copula PDF values in the upper and lower tail are relatively high, indicating the probability of TCs with MWS and TP simultaneously being strong or weak is higher than TCs with either MWS or TP being severe. (2) The maxima of conditional probability increases with MWS, indicating that the most probable TP is also strong when MWS is strong. (3) Here, TP∈[1000, 2000]×10⁸ m³ is defined as strong TP. When MWS ≤60 m/s, the conditional probability of strong TP increases with MWS; but when MWS >60 m/s, the conditional probability of strong TP increases with MWS before the threshold and decreases with MWS after the threshold. Each TP is associated with an MWS threshold, which increases with the concerned TP.[Conclusions] Our findings show that the construction and analysis of the joint probability distribution between MWS and TP lead to an improved understanding of the interaction relationship between TC hazardous wind and precipitation. This study also contributes to a comprehensive investigation of the TC multihazard destructiveness.

[Objective] Water is the core resource of the Xiong'an New Area. Thus, achieving scientific and efficient management of water-related affairs is a critical challenge that must be solved. Water-related affairs in the Xiong'an New Area involve numerous stakeholders; however, there is a lack of systematic empirical research from the perspective of cooperation among government departments, water companies, and water users. Accordingly, this study aims to analyze the integrated water management mechanism from the perspective of cooperation among all stakeholders. [Methods] This study presented an integrated water management structure from the perspective of stakeholder cooperation and revealed the role of stakeholders in the water management cooperation mechanism from a theoretical perspective. Furthermore, this study combined quantitative and qualitative empirical research methods to analyze the current situation of integrated water management among stakeholders in the Xiong'an New Area. A questionnaire was used to collect quantitative data, and expert interviews and project visits were conducted to collect qualitative data. [Results] The results indicate that it is critical to establish a cooperation mechanism that combines river basins and regions for stakeholders in water-related affairs. It is necessary to clarify the work processes and allocation of responsibilities and rights of all stakeholders, realize the coordination and linkage between river basins and regions, and effectively solve water replenishment, pollution control, flood control, environmental protection, and other issues in an integrated way. The realization of the elements of the cooperation mechanism of stakeholders in water affairs demonstrates that all stakeholders must focus on the establishment of common goals and mutual trust, optimization of resource element allocation, reduction of regulatory costs, and strengthening of public water management performance and social supervision. “The enthusiasm for implementation” is most closely related to other elements and can represent the overall cooperation level of stakeholders. Accordingly, establishing incentive/restraint mechanisms in the stakeholder cooperation mechanism can promote the active and effective implementation of the cooperation mechanism. [Conclusions] This study concludes that (1) to implement integrated management of water affairs, it is necessary to integrate water-related functions, specify the core position of water affairs management departments, achieve unified planning, dispatching, and management of water resources, and avoid inefficiency and weakening of management functions caused by departmental interest conflicts. In addition, it is necessary to establish an effective assessment mechanism, review the work effectiveness of the water affairs management department with multi-perspective and multi-level evaluation feedback, promote the efficiency of administrative operation with positive incentives, eliminate the phenomenon of lazy government and power rent-seeking, and ensure the healthy development of the water industry. (2) Establish sound laws and regulations for the water market, follow the operating rules of the market economy, and allow enterprises to obtain reasonable economic benefits. The water affairs management department should conduct supervision and management and provide positive incentives, guide the business behavior of enterprises, improve the long-term incentive mechanism of the market, and realize the scientific combination of the development, rational allocation, efficient usage, and effective protection of the water resources system in the Xiong'an New Area. (3) The integrated management of water affairs must enhance the effective participation mechanism of the public, strengthen the effective restraint of public supervision on water enterprises and management departments, enhance the trust of all stakeholders, promote consensus, and improve the service level through information disclosure and transparent management. The findings of this study can provide theoretical and practical references for cooperative management of water-related affairs by stakeholders.