Marshalling Yard Research Articles

ФОРМИРОВАНИЕ ОБЪЕКТИВНЫХ ПОКАЗАТЕЛЕЙ РАБОТЫ СОРТИРОВОЧНОЙ СТАНЦИИ НА ОСНОВЕ ДАННЫХ «ОТ КОЛЕСА»

The paper presents a new principle for forming freight marshalling yard indicators based on the use of data from various reading devices and sensors located on the station tracks (data “from the wheel”). The paper shows the relevance and objectivity of using the proposed approach, implementing the presented principles for obtaining real freight yard indicators. The implementation is presented on the basis of data generated by the system for monitoring and preparing information on the movements of wagons and locomotives at the station in real time. The difference between the results obtained as a result of implementing the proposed approach and the information generated in real certificates and reporting journals of Russian Railways JSC is shown. Hypotheses-descriptions of the difference between information “from the wheel” and information obtained by manual input of data on the movements of cars and locomotives are proposed. The conclusion describes further prospects for automation of calculation and forecasting of station operation based on data “from the wheel”.

О корректировке алгоритма расчета высоты сортировочной горки

At present the height of marshalling yards is calculated basing on the determination of the power of resistance to the movement of cars when rolling down a hill on definite conditions. Wherein the calculation norms of the main specific resistance to movement, used until present time, were accepted more than 40 years ago. Therefore, their use for the description of the modern car park driving characteristics may lead to the results of unsuitable current operating conditions, as well as to the increase of the emergency appearance when disbanding. The article suggests the adjustment of the algorithm of a marshalling yard height calculation based on the results of up-to-date researches of the main specific resistance to movement made by the specialists of the Siberian Transport University and JSC «NIIAS» and the correction of the methods of calculation of the height of the marshalling yard.

СИСТЕМА АВТОМАТИЧЕСКОГО РЕГУЛИРОВАНИЯ СКОРОСТИ ДВИЖЕНИЯ МАНЕВРОВОГО ЛОКОМОТИВА

The experience of developing automatic control systems for switchers at a marshalling yard is described. The structural diagram of the interaction of the locomotive onboard systems with the automatic control function is given. The algorithm of the mode of maintaining a given speed is presented and its description is given. The results of simulation modeling of the train pushing and splitting on the gravity hump with the implementation of the specified algorithm (with different speeds and weights of the train) are displayed.

Optimization of track distribution of industrial railway stations between car designations

Purpose. To improve the method for distributing the tracks of industrial railway stations for the accumulation of car groups between separate assignments. The optimization problem is to find such a distribution of classification work between the industrial marshalling yard and freight stations, as well as such a distribution of marshalling yard tracks between individual destinations, which ensures the minimum time expenditures on shunting work. Methodology. The studies were carried out using the methods of the theory of railway operation, simulation modeling and dynamic programming. Findings. The optimization problem of distribution of sorting work between the marshalling yard and freight stations of an industrial enterprise, as well as searching for such a distribution of marshalling yard tracks between individual destinations, which ensures the minimum time expenditures for shunting work, has been solved. Originality. The paper proposes a method for formalizing and solving the problem of distributing the tracks of industrial railway stations for the accumulation of car groups between individual destinations as a dynamic programming problem. Unlike the existing methods, where the number of tracks is considered as a constraint, in the proposed method, the number of tracks is an objective function argument of minimizing the duration of shunting operations, which improves the quality of the solutions obtained. Practical value. The method proposed in the paper, due to the rational distribution of the existing track arrangement of railway stations, makes it possible to reduce the time expenditures on the making- and breaking-up the trains and shunting transfers and, due to this, increase the carrying capacity of the stations, as well as reduce the cost of production of enterprises.

A rolling horizon approach for shunting operations – An emission oriented simulation study

Marshalling yards are nodes in rail networks to sort railcars from incoming trains to outgoing trains. To built outgoing trains in the correct sequence, railcars are shunted by shunting locomotives. Thereby, green house gas emissions are emitted as those locomotives are usually diesel powered. As the planning of shunting operations is a very complex problem, heuristics, so-called sorting strategies, are applied in practice. In this paper the effects of practically relevant sorting strategies on green house gas emissions are studied in a rolling horizon model. The rolling horizon model is used in a simulation study to investigate the effects of sorting strategies and input parameters (like the number and composition of ingoing and outgoing trains) on green house gas emissions. The results indicate that for different parameter constellations, different emission-optimal sorting strategies exist. Thus, sorting strategy selection should be done carefully depending on the operational conditions at the shunting yards.

Traffic of multi-car trains in marshalling yards

Developing rail transport is one of the world's greatest challenges. Rail transport reduces emissions and is the most energy efficient means of transport. An important element of the railways is a hump yard, where rolling stock is formed. The purpose of this article is to describe the mathematical apparatus for calculating the speed of a multiple unit train at a marshalling yard. As a calculation method, the articulated-axis model is used. In this model, the trailer is not seen as a material point, but as several physical bodies. Due to this model, it is possible to simulate multi-carriages moving along heterogeneous profile. It was found that for multi-car trailers the spread of the main co-protection will be lower than for single-car trailers. In addition, as a result of accounting for multi-car trains, the profile requirements are reduced when calculating marshalling yards. The results obtained can be used to design hump yards and automate existing hump yards.

Solving logistic tasks by parallelizing algorithms of the theory of direct decompositions of torsion-free abelian groups

The paper considers the principles of parallelization at marshalling yards and determines their importance. There are presented the methods for direct decompositions of torsion-free Abelian groups of finite rank. There are applied the concepts of “conditionally linear graphs” depicting railway trains and their characteristics, including “quasi-length”, which characterizes the length of the corresponding “quasi-graph”. There has been formalized a graphical approach to the redistribution of railcars of incoming trains at a marshalling yard for the formation of outgoing trains. The corresponding algorithms have been developed.

Fuzzy modelling of the transportation logistics processes

The relevance of mechanisms and fuzzy modeling methods used in transport and logistics processes is justified. The logic of the transport and logistics chains study by their decomposition into separate economic entities with subsequent synthesis, with taking into account their conflicting interests, is presented. The task of managing transport and logistics processes is set within the framework of the conceptual positions of the fuzzy sets theory: the use of linguistic variables, the concept of a fuzzy set, fuzzy inference, implemented on the basis of fuzzy sets operations. In this study, the fuzzy modeling on the bottom-up conclusions from the premises to the conclusion was used. Various methods of implication and defuzzification have been analyzed. An iterative procedure for managing transport and logistics chains and their links has been proposed, which ensures the adaptation of the process to the specified performance indicators. A calculated example is given for a marshalling yard as a link in the transport and logistics chain.

Simulation of railway marshalling yards using the methods of the queueing theory

Aim. The paper primarily aims to simulate the operation of railway transportation systems using the queueing theory with the case study of marshalling yards. The goals also include the development of the methods and tools of mathematical simulation and queueing theory. Methods. One of the pressing matters of modern science is the development of methods of mathematical simulation of transportation systems for the purpose of analyzing the efficiency, stability and dependability of their operation while taking into account random factors. Research has shown that the use of the most mature class of such models, the singlephase Markovian queueing systems, does not enable an adequate description of transportation facilities and systems, particularly in railway transportation. For that reason, this paper suggests more complex mathematical models in the form of queueing networks, i.e., multiple interconnected queueing systems, where arrivals are serviced. The graph of a queueing network does not have to be connected and circuit-free (a tree), which allows simulating transportation systems with random structures that are specified in table form as a so-called “routing matrix”. We suggest using the BMAP model for the purpose of describing incoming traffic flows. The Branch Markovian Arrival Process is a Poisson process with batch arrivals. It allows combining several different arrivals into a single structure, which, in turn, significantly increases the simulation adequacy. The complex structure of the designed model does not allow studying it analytically. Therefore, based on the mathematical description, a simulation model was developed and implemented in the form of software. Results. The developed models and algorithms were evaluated using the case study of the largest Russian marshalling yard. A computational experiment was performed and produced substantial recommendations. Another important result of the research is that significant progress was made in the development of a single method of mathematical and computer simulation of transportation hubs based on the queueing theory. That is the strategic goal of the conducted research that aims to improve the accuracy and adequacy of simulation compared to the known methods, as well as should allow extending the capabilities and applicability of the model-based approach. Conclusions. The proposed model-based approach proved to be a rather efficient tool that allows studying the operation of railway marshalling yards under various parameters of arrivals and different capacity of the yards. It is unlikely to completely replace the conventional methods of researching the operation of railway stations based on detailed descriptions. However, the study shows that it is quite usable as a primary analysis tool that does not require significant efforts and detailed statistics.

Concept of Digital Platform at Marshalling Yards

Implementation of the Industry 4.0 concept is considered in the context of automation of railway transport. The analysis refers to prerequisites for creation of a universal digital platform integrating automation systems at a marshalling yard.The example of JSC Russian Railways has contributed to describe the main goals of Digital Station concept, aimed at fusion of data from low-level local automation equipment. The presented functionality of the system for control and processing information on movements of wagons and locomotives at the station in real time (SCPI MWL RT) implements the set goals by integrating initial data from all automation and centralised traffic control systems operating at the station, checking it for consistency, eliminating information redundancy and generating in real time the current model of a marshalling yard regarding trains and wagons and based on data «from the wheel».Description of the existing functionality of SCPI MWL RT, implemented at a facility, is followed by the analysis of the advantages of this system for the railway cargo transportation network. The objective of the paper is to present some previously unpublished technical solutions for implementation of the specified functionality. The methods of the research are based on fusion of heterogeneous data received from floor devices, specialised video cameras, as well as from real-time wagon positioning models.It is shown that adoption of new technical solutions for SCPI MWL RT will allow to considerably improve the quality of planning of technological process of classifying railway wagons and of forecasting the need for infrastructure maintenance. Deep learning algorithms presented ensure functioning of the developed solutions in real time with high accuracy. Further steps described refer to implementation of a digital platform in the form of a digital twin of a marshalling yard, creating thus a prerequisite for development of an intelligent automatic machine to control the marshalling yard, as well as for further planned ways to implementation there-of.

Assessment of urban heat islands for land use based on urban planning: a case study in the main urban area of Xuzhou City, China

The urban heat island (UHI) effect is an important issue in urban planning. In this study, the framework of the land surface temperature (LST) and UHIindex for urban development land (UDL) based on urban planning in China was proposed to examine the spatiotemporal evolution of the LST and the UHIindex for the whole city as well as the LST and the UHIindex of UDL at four node stages (1995, 2003, 2014 and 2019), reflecting the process of urbanization. The results demonstrate that the UHIindex showed an overall trend of first decreasing and then increasing in the process of urbanization over 2 decades. The UHI is characterized by the evolution of spatial distribution from a local point-like aggregation (1995) to a linear expansion along the urban construction land (2003), then to patchy areas tending towards overall homogeneous coverage gradually expanding (2019). The LST increased yearly, but the UHIindex first decreased and then increased, while the average UHIindex and the LST of UDL in the overall relationship maintained good consistency each year. The industrial and logistics concentration area with railway marshalling yard as the core area is the most important patch to maintain the urban thermal pattern. The results provide a quantitative basis for the thermal environmental planning of UDL and a reference for research on UHI under different land planning and management systems in other countries and regions of the world.

Modeling of Railway Stations Based on Queuing Networks

Among the micro-logistic transport systems, railway stations should be highlighted, such as one of the most important transport infrastructure elements. The efficiency of the transport industry as a whole depends on the quality of their operation. Such systems have a complex multi-level structure, and the incoming traffic flow often has a stochastic character. It is known that the most effective approach to study the operation of such systems is mathematical modeling. Earlier, we proposed an approach to transport hub modeling using multiphase queuing systems with a batch Markovian arrival process (BMAP) as an incoming flow. In this paper, we develop the method by applying more complex models based on queuing networks that allow us to describe in detail the route of requests within an object with a non-linear hierarchical structure. This allows us to increase the adequacy of modeling and explore a new class of objects—freight railway stations and marshalling yards. Here we present mathematical models of two railway stations, one of which is a freight railway station located in Russia, and the other is a marshalling yard in the USA. The models have the form of queuing networks with BMAP flow. They are implemented as simulation software, and a numerical experiment is carried out. Based on the numerical results, some “bottlenecks” in the structure of the studied stations are determined. Moreover, the risk of switching to an irregular mode of operation is assessed. The proposed method is suitable for describing a wide range of cargo and passenger transport systems, including river ports, seaports, airports, and multimodal transport hubs. It allows a primary analysis of the hub operation and does not need large statistical information for parametric identification.

Моделирование крупнейшей в мире железнодорожной сортировочной станции с использованием теории массового обслуживания

The problem of scenario forecasting of the operation of railway stations in the conditions of changing traffic flow is considered. An approach to modeling based on the use of the queuing theory apparatus is proposed, which allows taking into account the presence of significant random impacts on the system operation. The largest railway marshalling yard in the world - Bailey Yard (Nebraska, USA) was chosen as the object. The article presents a mathematical model of its operation in the form of a queuing network, in which, unlike queuing systems, branching and circular movement of applications are allowed. This allows you to display various routes of the movement of cars in the structure of the station. To describe several incoming transport flows, a BMAP stream (Branch Markovian Arrival Process) is used, so it is possible to take into account the parameters of each of them. Analytical results for such mathematical objects are not known, so the model is studied numerically. The amount of traffic flow varies in a series of experiments. Based on the results obtained, the current and maximum capacity of the station, «bottlenecks» in its structure are determined and recommendations are developed to improve the efficiency of its operation.

World Experience of Railway Marshalling Yards: Current State, Trends and Prospects

World Experience of Railway Marshalling Yards: Current State, Trends and Prospects

Экономическое сравнение вариантов организации контрейлерного терминала на сортировочной станции

Objective: To carry out an economic comparison of alternative options for a piggyback terminal layout solution in a marshalling yard. Methods: Modern logistics, customer focus approach, synchromodality, system analysis, comparison of options, forecasting, project and situational management methods were used. Results: Scenario forecasting allowed us to assess the possible dynamic patterns of traffic volumes for three options. The position of the yard in the hub is characterized. The technical and technology design of a piggyback terminal are briefly discussed. The terminal location options based on the yard infrastructure are indicated. Schematic solutions with different terminal-yard junctions through turnout track N 22 (option 1) and N 16 of the Transfer Park (option 2) are proposed. We have analyzed benefits and drawbacks, calculated the cost of the marshalling yard development for each developed option at 2014 values. In particular, the itemized capital investments and operating costs of the marshalling yard stepwise development are calculated and presented in a tabular form. Practical importance: The comparative analysis results for a set of technical and economic indicators are presented. Using the method of comparing options for different indicators, option 1 was selected as the most rational in terms of the minimum cumulative costs

Thermomechanical damage to rolling stock wheels

Marshalling yards are a key part of the transportation process. Their precise operation determines the efficiency and safety of the transportation process, which, other things being equal, depend on the durability and safety of cars in real conditions, including during sorting processes on slides. Currently, during the dissolution of trains on low-power slides, shoe braking is used. This is cost-effective, but provokes the formation of thermomechanical damage on the surface of the wheels. These damages are called one-way sliders. The formation of sliders leads to downtime of cars during repairs and to the cost of restoring or manufacturing new wheels. The article presents a study of the effect of wheel sliding on the rail on the nature of thermal and mechanical damage to the wheels of rolling stock.

ORGANIZING WIRELESS NETWORK AT MARSHALLING YARDS USING THE BEE METHOD

Purpose. In general, today wireless networks are widely used as an alternative to wired, allowing you to connect multiple devices, both among themselves in the local and global Internet. However, at the present stage in Ukraine there is no widespread use of a wireless network at rail transport, therefore it is advisable to conduct research on the deployment of such a network, in particular, at a marshalling yard. Methodology. Using LocBS‑BeeCol program model written in Python according to the bee colony algorithm the optimal number of base stations (BS) of the wireless network and their location at the marshalling yards was determined, as well as research on the bee algorithm parameters was conducted. Input data of the LocBS‑BeeCol model are as follows: marshalling yard parameters (area, number of clients that need to be connected to base stations); wireless network parameters (base station coverage radius, maximum number of clients for one base station); parameters of the bee colony algorithm (number of scout bees, number of attempts to find the optimal solution using one bee). Findings. For marshalling yards of various capacities (small, medium and high), the optimal number of base stations of the wireless network was obtained with restrictions on the coverage radius of the base station and the number of clients connected to it. Thus, for example, to connect 300 clients at medium-sized marshalling yards with an area of 2500x500 m2, 93 base stations with a coverage radius of 50 m are needed. Originality. The quality of the obtained solutions significantly depends on the choice of the bee colony algorithm parameters. A study of the base stations number of the wireless network and search time for finding the optimal solution for different number of bees and the number of attempts to find the optimal solution using the bee for marshalling yards of various capacities was carried out. It was determined that an increase in the number of bees (from 10 to 50) and the number of attempts to find the optimal solution by a bee (from 10 to 50) improves the quality of the optimal solution (decrease in the number of base stations by an average of 6.5% and 9.3%), respectively. In addition, increase in the bee number (from 10 to 50) reduces the search time for the optimal solution by bees by an average of 1.8 times, while increase in the number of attempts to find the optimal solution by a bee (from 10 to 50) will increase search time for the optimal solution on average 2.14 times. Practical value. An algorithm and its software implementation have been developed, which make it possible to determine the required number of base stations and their location when deploying a wireless network at a marshalling yards. For marshalling yards with high capacity, when the coverage radius of the base station is doubled (from 50 to100 m), their number decreases by about half (from 136 to 64), while the time for finding the optimal solution by bees increases by 2.5 times (from 8.4 to 20.6 s).

Implementation of Intelligent Monitoring for the Marshalling Yard

The railway marshalling station occupies a central place in the technological chain of freight transportation processes, since the speed of processing trains at marshalling yards determines the volume and cost of transportation. Therefore, development of automation and computerization of sorting processes results in growing efficiency of freight transportation in general. The objective of the study is to formalize the problem of cars’ monitoring within the railway marshalling yard and to develop a method for solving it with the use of algorithms of recognizing and positioning of dynamic objects through the intelligent data analysis of streaming video. The article presents a new approach to solution of the problem of monitoring moving units in the hump (sorting) yard of marshalling stations. The article suggests core criteria for identifying speed and positioning of the railway wagons when they are running after been separated at the hump. The article specifies that monitoring of moving units at hump yard is less automated in comparison with the monitoring at the hump itself, and that confirms the relevance of the research. To get the problem of the automation monitoring of moving units in the hump yard solved, the authors have suggested an algorithm that is based on the image data intelligent analysis, that is on computer vision, and have described the model of its implementation at a station. The methods used are based on the theory of computer vision and are aimed at recognizing key dynamic objects in streaming video and at their subsequent positioning. The study has resulted in substantiation of acceptability of the use of computer vision in the process of separation and formation of trains. It is planned to proceed with further improvement of the presented approach to develop a software product allowing to objectify information about hump yard in order to increase the efficiency of targeted braking at the hump.

An Acoustic-Based Recognition Algorithm for the Unreleased Braking of Railway Wagons in Marshalling Yards

The abnormal braking of wagons is a challenging safety problem for operators at railway marshalling yard. This paper develops an acoustic-based technology to detect the unreleased braking of wagons during the uncoupling operation. Experiments have been conducted to collect the acoustic waves of wagons abnormal braking, as well as the background sounds like train whistling and wheel vibration. Before data collection, a wayside recording system and an experimental train composed of 5 different wagons have been prepared in the marshalling yard. The recognition algorithm consists of fast Fourier transform (FFT), feature extraction, template matching and support vector machine (SVM) classification. Based on the sample data of different acoustic waves, the FFT is firstly performed to obtain the frequency spectrum from original time-domain signals. Then the major spectrum features of different sounds are carefully extracted for SVM training through a newly-devised algorithm, where the features include the spectrum center, spectrum flux, energy peak and corresponding frequency. During the SVM training, classifiers are designed under the one-against-one strategy to guarantee the recognition accuracy. Given a test data, at most 3 SVM classifiers will be activated according to the decision matrix of template matching. Meanwhile, rules have been made to regulate the classification result considering different activation cases. Finally, a case study of all 12 sound categories has been performed to illustrate the application of proposed algorithm. Results show that the acoustic-based recognition algorithm is indeed reliable to identify wagons unreleased braking, with the global warning accuracy over 98%.

Neural Network for Forecasting Energy Consumption Load of a Railway Marshalling Yard

A multilayer neural network has been designed to forecast average daily energy consumption of a railway marshalling yard. The suggested model comprises a multilayer perceptron using 22 inputs, the n-th number of hidden layers and one output. The number of hidden layers in the neural network and neurons in them was chosen experimentally. A comparative selection of activation functions and training methods has allowed for all other parameters to achieve a minimum average relative error. Two types of loads corresponding to holidays (non-working) and working days were identified. An additional input node with binary coding and two nodes for coding the season were introduced due to a certain repeatability characterizing samples of prediction of loads of energy consumption of the marshalling yard depending on type of a day and on a season. As accounting of the dependence of the forecast on load values in previous days and years (dynamic dependencies) is most important factor, this neural network takes into account the average daily energy consumption during four days of the current period, precedingthe forecasted date, and the average daily power consumption during four days prior to this date during last three years.As a result, considering all factors and experimentally selected parameters of the neural network, the minimum resulting error of MAPE is about 1,4 %, which shows the advantage of the developed neural network in comparison with two other methods of solution of the problem, suggested by other researchers.