Flow Routing Research Articles

STUDY OF STABILITY OF TRAIN FLOWS ON HEAVILY USED FREIGHT RAILWAY REGION

The article examines the stability of freight trains in different periods of traffic at the landfillof the regional branch of "Odessa Railway" JSC "Ukrzaliznytsia", which is a "bottleneck" of the railway systemwith the largest seaports in Ukraine. It is offered to analyze the consolidated daily operational indicators onthe main routes of train flows: density at the train station (traffic density per 1 km, tons); average daily speedof trains (km / h); the number of freight trains that have passed (train). For a comprehensive analysis ofchanges in operational indicators in the low (I-III quarter) and high season (IV quarter) of traffic summarizedindicators in the sequence of train flows. This allowed us to identify the most influential train stations for thestability of train traffic. Regularities of influence of operational indicators on the general duration ofmovement of train streams are revealed. Based on the correlation analysis, the influence of passenger trafficon the duration of freight trains on differentroutes has been proved numerically. Correlations can be describedas strong and significant. The interaction of changes in operational indicators on different routes of train flowsat the investigated landfill was revealed. Significant impact on the stability of train flows occurs at trainstations, where sorting stations operate. Increasing the share of scheduled departures in 2019 and working toextend the service in 2020 has reduced the gap between the total duration of trains on the routes to acceptablevalues. A cluster diagram of the relationship between the impact of passenger traffic on the duration of freighttrains on different routes, which allows a comprehensive analysis of the interdependence of operationalperformance of sections in terms of changes in traffic intensity and redirection of trains on parallel lines.

Research on Real-Time Communication Algorithm of Substation Based on Time-Sensitive Network

A time-sensitive network (TSN) extends the conventional Ethernet to support time-sensitive data flow. Thus, it enables simultaneous transmission of high reliability (HR) flow, medium reliability (MR) flow, and low reliability (LR) flow on the same network, thereby improving the reliability of data transmission. A TSN is a symmetric network that connects sensors and other facilities. As a backbone network, it can efficiently connect the underlying sensors and other levels of facilities, as well as ensure the quality of service of the network. For modern supervisory control and data acquisition (SCADA) systems, several types of sensors are widely used. The acquisition cycle of sensors for different purposes varies significantly from milliseconds to seconds. Moreover, these data also have different real-time requirements. Based on satisfiability modulo theories (SMT), this study proposes a TSN routing and scheduling method by adding related scheduling constraints. Compared with other methods, the proposed method can realize the routing and scheduling of hybrid flow in a hyper period and consider MR flow and LR flow, which improves the feasibility and certainty of data flow interaction between substations.

Two-Level Capacitated Discrete Location with Concave Costs

In this paper, we study a general class of two-level capacitated discrete location problems with concave costs. The concavity arises from the economies of scale in production, inventory, or handling at the facilities and from the consolidation of flows for transportation and transshipment on the links connecting the facilities. Given the discrete nature of the problem, it is naturally formulated as a mixed-integer nonlinear program that uses binary variables for locational decisions and continuous variables for routing flows. We present an alternative formulation that only uses continuous variables and discontinuous functions, resulting in a nonlinear program with a concave objective function. Our main goal is to computationally compare these two modeling approaches under the same solution framework. In particular, we present an exact branch-and-bound algorithm that uses (integer) linear relaxations of the proposed formulations to optimally solve large-scale instances. The algorithm is enhanced with a cost-dependent spatial branching strategy and preprocessing step to improve its convergence. Extensive computational experiments are performed to assess the performance of the exact algorithm. Based on real location data from 3,109 counties in the contiguous United States, we also present a sensitivity analysis to showcase the impact of considering concave costs in location and assignment decisions.

Optimal deployment of virtual network functions for securing telecommunication networks against distributed denial of service attacks: A robust optimization approach

Distributed Denial of Service (DDoS) cyberattacks represent a major security risk for network operators and internet service providers. They thus need to invest in security solutions to protect their network against DDoS attacks. The present work focuses on deploying a network function virtualization based architecture to secure a network against an on-going DDoS attack. We assume that the target, sources and volume of the attack have been identified. However, due to 5G network slicing, the exact routing of the illegitimate flow in the network is not known by the internet service provider. We seek to determine the optimal number and locations of virtual network functions in order to remove all the illegitimate traffic while minimizing the total cost of the activated virtual network functions. We propose a robust optimization framework to solve this problem. The uncertain input parameters correspond to the amount of illegitimate flow on each path connecting an attack source to the target and can take values within a predefined uncertainty set. In order to solve this robust optimization problem, we develop an adversarial approach in which the adversarial sub-problem is solved by a Branch & Price algorithm. The results of our computational experiments, carried out on medium-size randomly generated instances, show that the proposed solution approach is able to provide optimal solutions within short computation times.

Electroconvective instability near an ion-selective surface: A mesoscopic lattice Boltzmann study.

Direct numerical simulations of electroconvection instability near an ion-selective surface are conducted using a mesoscopic lattice Boltzmann method (LBM). An electrohydrodynamic model of ion transport and fluid flow is presented. We numerically solve the Poisson-Nernst-Planck equations for the electric field and the Navier-Stokes equations for the flow field. The results cover Ohmic, limiting, and overlimiting current regimes, and they are in good agreement with the asymptotic analytical solution for the relationship between current and voltage. The influences of different ion transport mechanisms on the voltage-current relationship are discussed. The results reveal that the electroconvection mechanism is as important as other ion transport mechanisms in electrohydrodynamic flow. By comparing the contribution of different regions in the numerical domain, we find that the flow in the extended space charge layer is dominated by electroconvection. We also study the influences of multiple driving parameters, and the electrohydrodynamic coupling constant plays a dominant role in triggering convective instability. The flow pattern and ion concentration distribution are described in detail. Moreover, the route of flow from steady state to periodic oscillation and then to chaos is discussed.

Approaches for emission reduction in natural gas fueled direct-injection engines

A glow plug (GP) can serve as an effective ignition source in a heavy-duty direct-injection natural gas (DING) engine. Ignition performance can be improved by shielding the GP. The shield protects the GP from cooling by the injected natural gas (NG) jets and also traps NG next to the GP surface, acting as kind of pre-combustion chamber. Achieving rapid filing of the shield by a fuel jet and facilitating flame propagation out are key goals of shield design. However, previous studies found that emissions such as unburned CH4 and soot particles could be trapped inside the shield especially near its top end, contributing a large fraction to the engine exhaust. In this paper, new designs either controlling the NG amount entering the shield or improving the emission propagation out of the shield are proposed to solve the emission issues, and the impacts of these design changes on fuel injection and combustion emissions were computationally investigated. The base case includes an injector with nine 0.2 mm diameter nozzles and a diamond-pattern multi-opening GP shield. A new injector combining one smaller nozzle directed towards the GP shield and eight regular size nozzles was compared, while a new five-opening shield design adding a small opening on the top end of the diamond-pattern shield was studied. Compared to the base case, the new two-nozzle-size injector greatly reduced the amount of fuel injected into the shield, which solved the emission issues inside the shield. Over 35% and 95% reductions in the total mass of unburned CH4 and soot particles respectively were achieved. Furthermore, the additional opening for the new shield provides an alternative route for fuel flowing out of the shield during fuel injection. However, fuel injection is the main force for fuel motion inside the shield and highly affects the new flow route provided by the additional opening. The unburned CH4 and formed soot particles could not flow out of the shield through the additional opening once fuel injection is finished. Generally, an increase was found for the unburned CH4 and soot mass by using the new five-opening shield, compared to the base case.

Entropy-Based Flow and Sediment Routing in Data Deficit River Networks

Entropy-Based Flow and Sediment Routing in Data Deficit River Networks

Model of river flow routing on a continental scale with variable flow velocity

In the latest version of the climatic model of river flow formation, water transport along the river network to the mouth was carried out for each section of the Lena River and its tributaries at its constant rate. This paper presents two approaches to routing surface runoff with time-varying flow rates. The use of these approaches may allow the model to represent not only average multi-year flow rates, but also the ability to simulate floods and short-term fluctuations in river flow. Two numerical experiments were conducted: simulations of river flow with constant and variable velocities.

Maximum Flow Routing Strategy for Space Information Network With Service Function Constraints

In this paper, we investigate the maximum flow routing strategy with the service function chain (SFC) constraints in the space information networks (SINs), where a SFC consists of a specific ordered sequence of service functions, and the mission flow must go through these functions in a predefined order. The time-varying SIN is modeled by the time-expanded graph (TEG). We formulate the maximum flow routing strategy problem with the SFC constraints as a linear programming (LP) problem. Furthermore, for a large-scale SIN, as the complexity of solving the LP problem is still very high, we propose a novel low-complexity SFC-constrained graph theory based (SFC-GT) algorithm. Specifically, we formulate this problem as one special single commodity maximum flow problem, where this flow must satisfy the SFC constraints. We first define the SFC-constrained residual network and the SFC-constrained augmenting path. Afterwards, we iteratively search the SFC-constrained augmenting path and update the SFC-constrained residual network. Simulation results demonstrate our proposed SFC-GT algorithm can achieve near-optimal performance with much less complexity.

Geovisualization of Hydrological Flow in Hexagonal Grid Systems

Recent research has extended conventional hydrological algorithms into a hexagonal grid and noted that hydrological modeling on a hexagonal mesh grid outperformed that on a rectangular grid. Among the hydrological products, flow routing grids are the base of many other hydrological simulations, such as flow accumulation, watershed delineation, and stream networks. However, most of the previous research adopted the D6 algorithm, which is analogous to the D8 algorithm over a rectangular grid, to produce flow routing. This paper explored another four methods regarding generating flow directions in a hexagonal grid, based on four algorithms of slope aspect computation. We also developed and visualized hexagonal-grid-based hydrological operations, including flow accumulation, watershed delineation, and hydrological indices computation. Experiments were carried out across multiple grid resolutions with various terrain roughness. The results showed that flow direction can vary among different approaches, and the impact of such variation can propagate to flow accumulation, watershed delineation, and hydrological indices production, which was reflected by the cell-wise comparison and visualization. This research is practical for hydrological analysis in hexagonal, hierarchical grids, such as Discrete Global Grid Systems, and the developed operations can be used in flood modeling in the real world.

INTELLIGENT SYSTEM FOR AUTOMATION SEARCH OF PUBLIC TRANSPORT ROUTES

This article is devoted to automation of search of routes of passenger flows of inhabitants of the city on the basis of routes of public transport. To do this, it is proposed to use satellite data that reflect the movement of passengers. Based on the analysis of data arrays of information on the movement of cellular subscribers and the use of message messages to determine the effectiveness of passenger routes of public transport, the article proposes to create a system of automatic search of public transport routes, which includes different classes of charts and data bases. You can use data from cellular operators to do this. This can increase the accuracy of certain traffic volumes and the ability to monitor them in real time. Reliable information on the routes of urban public transport allows to determine passenger flows and efficiently perform transport services. The main requirements for modeling the city’s passenger traffic are presented. Methods of obtaining data on determining the city’s passenger traffic and public transport are considered. Documentation for the creation of the ISASR (Intelligent System for Automation Search of Routes) project has been developed. The MVC (Model-View-Controller) architectural template was used to develop the project. Class diagrams and precedent diagrams have been developed for the model. Database structures have been created and vehicle types and user types have been defined. Algorithms for finding routes for different situations, with different latitude and longitude coordinates, as well as different number of stops and transfers have been developed.

An Enhanced Routing and Scheduling Mechanism for Time-Triggered Traffic with Large Period Differences in Time-Sensitive Networking

In the field of the automotive area as well as industrial control, real-time communication requires deterministic delivery with low delay and bounded jitter. Real-time communication in these networks requires transmission schedule and routing, which is an NP-hard problem. In this paper, we present an offline routing and scheduling method based on integer linear programming (ILP), with a flow preprocessing step to explore the period correlation of time-triggered (TT) traffic in time-sensitive networking (TSN). First, a multiperiod flow routing and scheduling algorithm based on flow classification is proposed to improve the scheduling success rate and reduce execution time. The flow classification technique obtained a more fine-grained TT traffic classification, which can be superimposed on any routing and scheduling algorithms. Second, an adaptive period compensation scheduling algorithm based on flow classification is proposed in simple network architecture conditions. The evaluations demonstrate that the proposed algorithms improve scheduling success rate and reduce execution time compared with baseline methods in all test cases. In addition, we can adapt our different proposed algorithms in different network architecture conditions to schedule various flows with different periods and sizes.

Representing Normal and Abnormal Physiology as Routes of Flow in ApiNATOMY.

We present (i) the ApiNATOMY workflow to build knowledge models of biological connectivity, as well as (ii) the ApiNATOMY TOO map, a topological scaffold to organize and visually inspect these connectivity models in the context of a canonical architecture of body compartments. In this work, we outline the implementation of ApiNATOMY’s knowledge representation in the context of a large-scale effort, SPARC, to map the autonomic nervous system. Within SPARC, the ApiNATOMY modeling effort has generated the SCKAN knowledge graph that combines connectivity models and TOO map. This knowledge graph models flow routes for a number of normal and disease scenarios in physiology. Calculations over SCKAN to infer routes are being leveraged to classify, navigate and search for semantically-linked metadata of multimodal experimental datasets for a number of cross-scale, cross-disciplinary projects.

Difficulties In Qualifying for Kidney Transplantation In a Highly Immunized Patient With Urinary Tract Defects

• The immunization of patients with kidney insufficiency reduces the chances of being qualified for transplantation and increases the risk of organ rejection. • According to the recommendations of Kidney Disease: Improving Global Outcomes 2020, each event leading to patient sensitization should be communicated to the laboratory testing the patient's anti-HLA in advance, as the sensitization history is necessary for the correct analysis of antibody levels, which are dynamic and not always reflected in panel reactive antibody tests. • Highly immunized patients should not be excluded from transplant, and thanks to the available methods of removing circulating DSAs and reducing their production, their waiting time for transplant can be significantly reduced. • Concomitant defects of the urinary tract, which were once a contraindication to transplant, today are only an obstacle at the time of kidney transplant. • In patients with impaired urinary flow, it may be necessary to create an alternative route of urine flow. • In the case of patients who have undergone a cystectomy, a good solution may be to divert the urine using the Bricker method, which consists of creating a urostomy using a fragment of the small intestine.

Location identification of river bathymetric error based on the forward and reverse flow routing

AbstractRiver bathymetric data is fundamental to water flow simulation. In practice, due to measurement uncertainty and riverbed erosion and deposition, river bathymetric errors are inevitable. Therefore, identifying major cross sections with large bathymetric errors is of great significance. In this study, forward and reverse flow routing models were developed and then applied to obtain two different water stages for a specific cross section, which were respectively propagated from the upstream and downstream boundaries. The spatial variation of differences between the two calculated water stages was compared to quantify the influence of bathymetric errors, and then used as an indicator for the location identification of the bathymetric errors. After being tested and verified in a hypothetical river case, the identification method was then applied to the Xunjiang River case. The results show that the proposed method can effectively identify the cross sections with large bathymetric errors, and the identification performance is related to the flow magnitude. The research is valuable and practical to the improvement of river bathymetric data and the accuracy of water flow simulation.

Potential of the Coupled WRF/WRF-Hydro Modeling System for Flood Forecasting in the Ouémé River (West Africa)

Since the beginning of the 2000s, most of the West-African countries, particularly Benin, have experienced an increased frequency of extreme flood events. In this study, we focus on the case of the Ouémé river basin in Benin. To investigate flood events in this basin for early warning, the coupled atmosphere–hydrology model system WRF-Hydro is used, and analyzed for the period 2008–2010. Such a coupled model allows exploration of the contribution of atmospheric components into the flood event, and its ability to simulate and predict accurate streamflow. The potential of WRF-Hydro to correctly simulate streamflow in the Ouémé river basin is assessed by forcing the model with operational analysis datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF). Atmospheric and land surface processes are resolved at a spatial resolution of 5 km. The additional surface and subsurface water flow routing are computed at a resolution of 500 m. Key parameters of the hydrological module of WRF-Hydro are calibrated offline and tested online with the coupled WRF-Hydro. The uncertainty of atmospheric modeling on coupled results is assessed with the stochastic kinetic energy backscatter scheme (SKEBS). WRF-Hydro is able to simulate the discharge in the Ouémé river in offline and fully coupled modes with a Kling–Gupta efficiency (KGE) around 0.70 and 0.76, respectively. In the fully coupled mode, the model captures the flood event that occurred in 2010. A stochastic perturbation ensemble of ten members for three rain seasons shows that the coupled model performance in terms of KGE ranges from 0.14 to 0.79. Additionally, an assessment of the soil moisture has been developed. This ability to realistically reproduce observed discharge in the Ouémé river basin demonstrates the potential of the coupled WRF-Hydro modeling system for future flood forecasting applications.

Monitoring and modeling sediment transport in space in small loess catchments using UAV-SfM photogrammetry

Sediment transport rates are widely used in studies of soil erosion, hydrological simulation, and regional ecological assessment. Although traditional field hydrological stations can provide a global sediment transport rate for observation areas, quantifying sediment transport rates in space is still challenging. This study presents a work frame for monitoring and modeling sediment transport in space using recently ongoing UAV-SfM photogrammetry. First, the DEMs of difference (DoDs) were obtained by repeated UAV surveys. Then, we used the root mean square error (RMSE) and precision map (spatially distributed errors) to detect topographic changes at different confidence levels and analyzed the relations between detected changes and the thresholding of confidence level. Finally, we compared different routing solutions for inferring the sediment transport rates in space based on the observed topographic changes. Results show that the thresholding of confidence level will lose observations and may underestimate global sediment transport rates. The sensitivity of observation loss to the confidence level by using the precision map is lower than that by using RMSE, suggesting that the use of the precision map is more suitable for topographic change detection. In terms of the spatially distributed sediment transport rates, the multiple flow routing based on slope exponent (MFD-se) shows superior performance than the multiple flow routing based on maximum downslope gradient (MFD-md) and eight-node (D-8) routing. The negative sediment transport in the study areas ranges from 2.53% to 7.85% by using MFD-se routing. Moreover, the use of thresholding of confidence level is beneficial to reduce negative transport. The proposed work frame can conveniently provide a detailed spatial distribution of sediment transport rates, which would provide a new perspective for studies of earth surface processes.

Rangeland hillslope lengths: A case study at the Walnut Gulch Experimental Watershed, southeastern Arizona

Rangeland hillslopes provide much of the sediment supplied to channel systems and their lengths exert a fundamental constraint on hillslope diffusive processes. However, information regarding lengths of rangeland hillslopes, and how best to estimate them, is limited. In this study, three groups of watersheds (10 in total) were selected from the Walnut Gulch Experimental Watershed according to their geology, soil and vegetation characteristics. Group 1 watersheds were at lower elevations dominated by shrubs, Group 3 were at high elevations dominated by grass, and Group 2 were mixed shrub and grass. Their hillslope lengths were calculated from 1 m-resolution DEMs using three methods: a flow routing algorithm, slope-area relationships, and inverted relationship with drainage density. Parameters that characterize the current watersheds, including Hack's exponent and coefficient, watershed shape coefficient, channel concavity and steepness, and surface roughness, were quantified and related to hillslope lengths. Results shows: (1) estimated hillslope lengths were different for the three methods and between the three groups of watersheds; (2) hillslope lengths that measured from the flow routing algorithm for the ten selected watersheds primarily ranged from 30 to 100 m, with a median value of 63.0 m, which was 20%–50% greater than those derived from slope-area plots or drainage densities; (3) hillslope lengths estimated from the flow routing method were greater in Group 3 watersheds than in Group 2 and then in Group 1 watersheds. We attributed these differences in hillslope lengths to the historic epeirogenic pulses, watershed and drainage network morphology, and differences in vegetation characteristics; (4) measured hillslope lengths from the flow routing algorithm were best correlated with hillslope relief, then surface roughness, channel steepness and concavity. These results would benefit the applications of hydrological and erosion models in rangelands.

Patient-Flow Analysis for Planning a Focused Hospital Layout: Tampere Heart Hospital Case.

The objective of this study is present how a patient movement-based patient-flow analysis is performed for planning the new Heart Hospital of Tampere University Hospital and how patient transfer distances can be shortened by this method. The Heart Hospital had served patients as a service line organization for years. However, the Heart Hospital layout rather looked like functional layout instead of service line layout because the units of the Heart Hospital have been spread out around the large university hospital campus. The flow routes of patients treated over the course of 1 year were analyzed by information technology systems in the hospital planning phase. Then, the proximity ranking of the main functions of the Heart Hospital was made. Layout planning was performed based on the proximity ranking. Nine months after the opening of the new Heart Hospital, the distances between the various hospital functions were calculated for the old Heart Hospital and the new one. In the old Heart Hospital, patients' transfer distance was 5,654 km (3,513 miles), while the corresponding figure for the new Heart Hospital was 3,797 km (2,359 miles), which means the distance was reduced by 33%. The patient-flow analysis works as it generated substantially shorter patient transfer distances in the new Heart Hospital. Shorter distances have supported more fluent patient flows that, in turn, has contributed higher productivity and quality of care.

Analysis and Design of the Split-Capacitor-Based Sub-Modules Equipped for Hybrid Modular Multilevel Converter

The hybrid modular multilevel converter (MMC) is always featured and profited by the merits of the equipped power valves. Referring to this, a novel hybrid MMC topology equipped with the split-capacitor-based sub-modules (SCSMs) on the AC side is proposed. It aims to increase the utilization of the DC bus voltage with DC fault blocking capability. Especially compared to the hybrid MMC equipped with the full-bridge-based sub-modules (FBSMs) on the AC side, smaller power losses can be achieved for the proposed hybrid MMC, due to the reason that only one semiconductor device of the SCSM is inserted into the current flow route. Structurally, the proposed converter mainly consists of the half-bridge-based sub-module (HBSM) stacks and SCSM stacks. The HBSMs located on the DC converter side of the proposed hybrid MMC are in charge of exchanging active powers, while the SCSMs located on the AC converter side are in charge of shaping the circuit waveforms. Additionally, profited by the specific structure of the SCSM, the DC fault current could be cut off by imposing inversed voltages collected from the SCSM capacitor voltages on the uncontrollable diodes of the IGBTs. For the deep study, a detailed mathematical model and modulation control of the proposed hybrid MMC are analyzed. In addition, an analysis of the balancing control for SCSMs is also provided. Finally, the simulation and experimental results are proposed to verify the effectiveness of the theoretical analysis.