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Identifying critical links is of great importance for ensuring the safety of the cyber-physical power system. Traditional electrical betweenness only considers power flow distribution on the link itself, while ignoring the local influence of neighborhood links and the coupled reaction of information flow on energy flow. An identification method based on electrical betweenness centrality and neighborhood similarity is proposed to consider the internal power flow dynamic influence existing in multi-neighborhood nodes and the topological structure interdependence between power nodes and communication nodes. Firstly, for the power network, the electrical topological overlap is proposed to quantify the vulnerability of the links. This approach comprehensively considers the local contribution of neighborhood nodes, power transmission characteristics, generator capacity, and load. Secondly, in communication networks, effective distance closeness centrality is defined to evaluate the importance of communication links, simultaneously taking into account factors such as the information equipment function and spatial relationships. Next, under the influence of coupled factors, a comprehensive model is constructed based on the dependency relationships between information flow and energy flow to more accurately assess the critical links in the power network. Finally, the simulation results show the effectiveness of the proposed method under dynamic and static attacks.

The primary concern of managers in logistics management is how market demand can be satisfied. The inventory in the transfer center of a distribution network plays a key role in meeting customer demands. This study focuses on evaluating the system reliability of a stochastic delivery-flow distribution network (SDDN) with inventory. An SDDN is composed of nodes and routes, where each node denotes a vendor, transfer center, or market and each route connects a pair of nodes. Along each route, there is a carrier whose available capacity is stochastic. Different from previous issues regarding system reliability, this study does not consider the vendor (source) and market (sink) but also the amount of stocks in transfer center is included. If the market demand cannot be met by inventory in transfer center, then vendors must meet the remaining demand to satisfy the market. Therefore an algorithm is developed in terms of minimal paths to evaluate system reliability, which is defined as the probability that the SDDN with stocks can satisfy the market demand from multiple vendors and transfer centers to the market under budget constraints. A numerical example is given to illustrate this proposed algorithm.

The ever-increasing travel demand has brought great challenges to the organization, operation, and management of the subway system. An accurate estimation of passenger flow distribution can help subway operators design corresponding operation plans and strategies scientifically. Although some literature has studied the problem of passenger flow distribution by analyzing the passengers’ path choice behaviors based on AFC (automated fare collection) data, few studies focus on the passenger flow distribution while considering the passenger–train matching probability, which is the key problem of passenger flow distribution. Specifically, the existing methods have not been applied to practical large-scale subway networks due to the computational complexity. To fill this research gap, this paper analyzes the relationship between passenger travel behavior and train operation in the space and time dimension and formulates the passenger–train matching probability by using multi-source data including AFC, train timetables, and network topology. Then, a reverse derivation method, which can reduce the scale of possible train combinations for passengers, is proposed to improve the computational efficiency. Simultaneously, an estimation method of passenger flow distribution is presented based on the passenger–train matching probability. Finally, two sets of experiments, including an accuracy verification experiment based on synthetic data and a comparison experiment based on real data from the Beijing subway, are conducted to verify the effectiveness of the proposed method. The calculation results show that the proposed method has a good accuracy and computational efficiency for a large-scale subway network.

Aiming at the problem that the flow rate of the two cavities of the differential cylinder does not match and it is not easy to achieve pump control, the team proposed the asymmetrical distribution principle of the axial piston pump with three ports, which can compensate for the flow difference between the two cavities of the differential cylinder without auxiliary components. Based on this principle, a new type of valve plate structure is designed by using the residual compression method. The pump performance is analyzed by PumpLinx simulation and experiment; the influence of the transition zone structure on the pressure and flow characteristics of the piston pump is researched. The basic characteristics of the pump such as pressure, flow, and noise under different working conditions were tested on the experimental platform, and the rationality of the new structure was verified. The new flow distribution scheme can not only compensate the flow difference of the differential cylinder, but also output two different pressures, which realizes the ideal effect of the hydraulic pump directly controlling the differential cylinder. The research work lays a theoretical foundation for the realization of the pump-controlled volumetric direct drive system.

The article presents an analysis of current (during the period 1985–2022) and projected (during the period 2025–2099) changes in the hydrological regime of the Buktyrma, Yesil, and Zhaiyk river basins in Kazakhstan under the conditions of global climate change. This study is based on the integration of data from General Circulation Models (GCMs) of the sixth phase of the CMIP6 project, socio-economic development scenarios SSP2-4.5 and SSP5-8.5, as well as the results of hydrological modelling using the SWIM model. The studies were carried out with an integrated approach to hydrological change assessment, taking into account scenario modelling, uncertainty analysis and the use of bias correction methods for climate data. A calculation method was used to analyse the intra-annual distribution of runoff, taking into account climate change. Detailed forecasts of changes in runoff and intra-annual water distribution up to the end of the 21st century for key water bodies in Kazakhstan were obtained. While the projections of river flow and hydrological parameters under CMIP6 scenarios are actively pursued worldwide, few studies have explicitly focused on forecasting intra-annual flow distribution in Central Asia, calculated using a methodology appropriate for this region and using CMIP6 ensemble scenarios. There have been studies on changes in the intra-annual distribution of runoff for individual river basins or local areas, but for the historical period, there have also been studies on modelling runoff forecasts using CMIP6 climate models, but have been very few systematic publications on the distribution of predicted intra-annual runoff in Central Asia, and this issue has not been fully studied. The projections suggest an intensification of flow seasonality (1), earlier flood peaks (2), reduced summer discharges (3) and an increased likelihood of extreme hydrological events under future climatic conditions. Changes in the seasonal structure of river flow in Central Asia are caused by both climatic factors—temperature, precipitation and glacier degradation—and significant anthropogenic influences, including irrigation and water management structures. These changes directly affect the risks of flooding and water shortages, as well as the adaptive capacity of water management systems. Given the high level of water management challenges and interregional conflicts over water use, the intra-annual distribution of runoff is important for long-term planning, the development of adaptation measures, and the formulation of public policy on sustainable water management in the face of growing climate challenges. This is critically important for water, agricultural, energy, and environmental planning in a region that already faces annual water management challenges and conflicts due to the uneven seasonal distribution of resources.

In this paper, the flow characteristics of a continuous-type liquid–liquid pintle injector are described, focusing on the differential impact of a non-uniform center-flow distribution on single- and bi-injection methodologies as well as the cavitation effect on the spray angle. Using cold-flow experiments, jet-type flows of the center propellant caused by a non-uniform flow distribution were observed during a single injection. This resulted in an augmented pressure drop, as opposed to the flow characteristics of uniform single-film injection. By contrast, bi-injection modalities exhibited a substantial reduction in the pressure drop of the center propellant, underscoring a more equitable flow distribution. Moreover, the occurrence of cavitation in the center propellant was found to markedly affect the spray angle. By considering the injection exit area reduction caused by cavitation, the spray-angle prediction accuracy increased. The findings of this study are expected to reveal the interplay between flow distribution and pressure drop as well as that between cavitation and the spray angle in pintle injectors. Through this understanding, this study provides crucial considerations for the development of more efficient propulsion systems.

A theoretical model for the calculation of thermal elastohydrodynamic lubrication performance of the flow distribution pair of piston pumps is established, which is composed of the oil film pressure governing equation and energy equation, and solved by means of numerical solution and simulation. We carry out quantitative analysis of the influence of various parameters on the thermal elastohydrodynamic lubrication characteristics of the flow distribution pair. The results indicate that both the oil film thickness and the cylinder tilt angle of the flow distribution pair vary in a periodic manner. The increase in the rotational speed of the cylinder block will increase the film thickness of the oil film and reduce the fluctuation, and the inclination angle of the cylinder block and its fluctuation amplitude will decrease. An increase in working pressure will lead to a decrease in the average oil film thickness, an increase in fluctuations, and an elevation in both the tilt angle of the cylinder block and its fluctuation amplitude. The increase in the rotational speed of the cylinder block and the increase in the working pressure will lead to the increase in the viscous friction dissipation of the flow distribution pair, the increase in the oil film temperature and the increase in the leakage. The reduction in the sealing belt will lead to the reduction in oil film friction torque and leakage.

We present a pioneering investigation into the relation between passenger flow distribution and network properties in public transport systems. The methodology is designed in a reverse engineering fashion by utilizing passively measured passenger flow dynamics over the entire network. We quantify the properties of public transport networks using a range of centrality indicators in the topological representations of public transport networks with both infrastructure and service layers considered. All the employed indicators, which originate from complex network science, are interpreted in the context of public transport systems. Regression models are further developed to capture the correlative relation between passenger flow distribution and several centrality indicators that are selected based on the correlation analysis. The primary finding from the case study on the tram networks of The Hague and Amsterdam is that the selected network properties can indeed be used to approximate passenger flow distribution in public transport systems to a reasonable extent. Notwithstanding, no causality is implied, as the correlation may also reflect how well the supply allocation caters for the underlying demand distribution. The significance and relevance of this study stems from two aspects: (1) the unraveled relation provides a parsimonious alternative to existing passenger assignment models that require many assumptions on the basis of limited data; (2) the resulting model offers efficient quick-scan decision support capabilities that can help transport planners in tactical planning decisions.

The article discusses the developed methods for accounting for stochastic water consumption, as well as mathematical models for accounting for stochastic water consumption in water supply and distribution systems. Due to the fact that pipeline engineering networks are non-linear, we will first determine the conditions for their linearization, and then we will show the solution of the problem for the resulting linearized network. The objective of this work is to connect the parameters of the stochastic process of water consumption from the network.

In the extensive urban rail transit network, interruptions will lead to service delays on the current line and spread to other lines, forcing many passengers to wait, detour, or even give up their trips. This paper proposes an event-driven simulation method to evaluate the impact of interruptions on passenger flow distribution. With this method, passengers are regarded as individual agents who can obtain complete information about the current traffic situation, and the impact of the occurrence, duration, and recovery of interruption events on passengers’ travel decisions is analyzed in detail. Then, two modes are used to assign passenger paths: experience-based pre-trip mode and response-based entrap mode. In the simulation process, the train is regarded as an individual agent with a fixed capacity. With the advance of the simulation clock, the network loading is completed through the interaction of the three agents of passengers, platforms, and trains. Interruption events are considered triggers, affecting other agents by affecting network topology and train schedules. Finally, taking Chongqing Metro as an example, the accuracy and effectiveness of the model are analyzed and verified. And the impact of interruption on passenger flow distribution indicators such as inbound volume, outbound volume, and transfer volume is studied from both the individual and overall dimensions. The results show that this study provides an effective method for calculating the passenger flow distribution of an extensive urban rail transit network in the case of interruption.