Serbian Railways Research Articles

Fly ash and slag utilization for the Serbian railway substructure

Approximately 7 million tons of fly ash and slag are produced in thermal power plants in Serbia every year, only 3% of which is used in the cement industry. About 300 million tons of the ash-slag mixture are disposed in landfills, occupying an area of approximately 1600 hectares and generating environmental issues. Fly ash from Serbian power plants has pozzolanic properties and due to low concentration of calcium compounds (less than 10% CaO), they do not have self-cementing properties. According to the ASTM C618-15, this ash is from class F. According to the European Standard EN 197-1:2011, this ash is siliceous (type V) ash. From April 2014 to May 2015, an investigation of engineering properties of fly ash and mixtures of fly ash and slag from landfill (without or with binders of cement/lime) was conducted at the Laboratory of Soil Mechanics at the Faculty of Civil Engineering of the University of Belgrade (Serbia) and at the Institute for Testing of Materials – IMS Institute in Belgrade. The laboratory test results were showed in the study ‘Utilization of fly ash and slag produced in the TPP JP EPS thermal power plants for construction of railways’. Four kinds of waste materials from Serbian power plants were laboratory tested: (a) an ash-slag mixture from landfills at the ‘Nikola Tesla A’ thermal power plant; (b) fly ash from silos in the ‘Nikola Tesla B’ thermal power plant; (c) an ash-slag mixture from landfills at the ‘Kostolac A’ and ‘Kostolac B’ thermal power plants and ‘Srednje kostolačko ostrvo’ landfill; (d) fly ash from the ‘Kostolac’ thermal power plant. The following physical and mechanical properties of ash and mixtures were investigated: grain size distribution, Atterberg limits, specific gravity, moisture-density relationship, shear strength parameters in terms of effective stresses, California Bearing Ratio (CBR), and deformation parameters. The paper presents the results of laboratory tests of the materials with and without binders, and based on the laboratory results and previous research, the paper presents possibilities of using fly ash and slag for the construction of railway substructure in the planned construction and reconstruction of railway network in Serbia. The obtained results indicate that tested fly ash and ash-slag mixture have met the technical requirements and that they have the potential to be used in railway substructure.

The framework for research of operators' functional suitability and efficiency in the control room

IntroThis paper presents the research on operators' functional suitability and efficiency in the Railway Traffic Control Room of the Serbian Railway Company in Niš. ObjectiveThe objective of this paper is to improve the working abilities of operators, and to achieve more human and rational control room design. MethodA total sample is n = 41. These are the operators who participated in the ergonomic evaluation of determining factors. A detailed analysis of the functional state of operators and operators' working movements at the control desk was undertaken in respect of the smaller sample of nineteen operators, randomly selected from the total sample. Based on the analytical-synthetic model of research, the ergonomic assessment of functional suitability and efficiency of the operator is formed. ResultsThe following results are obtained: the functionality parameter; the time for information search and reading symbols; the symptoms of visual, muscle and mental fatigue of operators; and the number of instruments in the field of view of the operator. ConclusionThe results of the analysis are used to identify ergonomic recommendations for enhancing the human and technical-technological productivity of work in the control room.

SARIMA modelling approach for railway passenger flow forecasting

In this paper, railway passenger flows are analyzed and a suitable modeling method proposed. Based on historical data composed from monthly passenger counts realized on Serbian railway network it is concluded that the time series has a strong autocorrelation of seasonal characteristics. In order to deal with seasonal periodicity, Seasonal AutoRegressive Integrated Moving Average (SARIMA) method is applied for fitting and forecasting the time series that spans over the January 2004 – June 2014 periods. Experimental results show good prediction performances. Therefore, developed SARIMA model can be considered for forecasting of monthly passenger flows on Serbian railways. First Published Online: 7 Mar 2016

Analysis of the process related to the operations management of the rail traction vehicles in JSC 'Serbian Railways'

Analysis of the process related to the operations management of the rail traction vehicles in JSC 'Serbian Railways'

Marketing communication in the area of breast and cervical cancer prevention.

Innovative marketing campaigns and promotional activities can successfully contribute to the improvement of public health by raising the level of general knowledge about health issues and benefits that the change of habits, eradication of undesirable behaviour and regular medical controls have. The focus should be on continuous marketing communication through various mass media or direct communication between medical staff and patients. The aim of this paper was to define the role that various communication channels have in the process of informing and educating the target group in case of breast and cervical cancer prevention. The survey based on polling a sample of 2,100 female patients of the Serbian Railways Medical Centre was conducted in the period October- December 2013. The questionnaire included questions about demographic characteristics, prevention habits of women, their level of information on that topic and communication channels they prefer. There is a difference among respondents' awareness level about preventive measures depending on demographic and geographical criteria. The results indicate the existence of variations in frequency of performing gynaecological examinations and Pap tests depending on different age, educational and residential groups. Although the largest percentage of women stated familiarity with the way of performing breast self-examination (78%), the majority of them had never performed mammography or ultrasonography (67%). The greatest number of women were informed about the possibility of preventing breast and cervical cancer by posters or brochures in health institutions (71%) and mass media--television on the first place (74%), then specialized magazines about health (48%), radio (48%), web sites about health (42%), and daily newspapers (34%). The respondents consider the Ministry of Health and health institutions as the most responsible subjects for education of women about cancer prevention, while the self-initiative was given the least importance. Determined informing habits of the target group, their prevention habits and attitudes on the subject should be used as the basis for planning and implementation of prevention marketing campaigns that would be the most effective.

A hybrid model for forecasting the volume of passenger flows on Serbian railways

The accuracy of predicting the volume of railway passenger flows is very significant because of the vital role in the basic functions of transportation resources management. Although dealing with this problem is very often based on the use of the neural networks, the uncertainty which dominates in the functioning of transportation systems is of great significance. The neural networks have been used for the time-series prediction with good results. This research compared two methods the parametric and the non-parametric approach. This study aims at presenting a hybrid model based on the integration of the genetic algorithm (GA) and the artificial neural networks (ANN) for forecasting the monthly volume of passengers on the Serbian railways. This innovative hybrid demonstrates how the genetic algorithms can be used to optimize the network architecture. By applying the idea of genetic algorithms in the neural networks, the integration is used so that on the basis of the input data, the selected population represents the number of neurons in the middle. In order to assess performances, the developed approach is compared to the traditional SARIMA model and the proposed method GAANN is better.

A Site Selection Model for Wayside Train Monitoring Systems at Serbian Railways

To remain competitive in a transport market, railway needs to increase reliability and to reduce the transport costs. Timely detection of a fault or defect can prevent a possible accident and can reduce maintenance costs. This paper presents a model for selection of locations for wayside train monitoring systems that are used to detect faults on the wagons. We present two models: first, based on multi-criteria decision making method is used for selecting a macro location, and second model based on fuzzy logic is used to determine a micro location of a wayside train monitoring system work station on Serbian rail network.

Analyzing passenger train arrival delays with support vector regression

We propose machine learning models that capture the relation between passenger train arrival delays and various characteristics of a railway system. Such models can be used at the tactical level to evaluate effects of various changes in a railway system on train delays. We present the first application of support vector regression in the analysis of train delays and compare its performance with the artificial neural networks which have been commonly used for such problems. Statistical comparison of the two models indicates that the support vector regression outperforms the artificial neural networks. Data for this analysis are collected from Serbian Railways and include expert opinions about the influence of infrastructure along different routes on train arrival delays.

NEURAL NETWORK BASED MODEL FOR PREDICTING THE NUMBER OF SLEEPING CARS IN RAIL TRANSPORT

A Decision Support System based on Artificial Neural Network is developed to forecast the number of sleeping cars in rail transport. The inputs to the system consist of train route, month, type of sleeping car, number of berths (supply), number of departures, ticket price and GDP, while the output of the neural network is the number of sold tickets (demand). By comparing the results obtained through the model with those resulting from historical data, it has been found that the developed model is highly compatible with reality. The developed Decision Support System could be used for capacity planning purposes, because it is important for a rail operator to know in advance how many sleeping cars have to be available. All considered data are obtained from Serbian Railways.

RAILWAY PROJECTS EVALUATION WITH DYNAMIC PRIORITIES – SERBIA CASE STUDY

Strategic decisions, such as transport investments, depend on a number of factors of different relevance that are often changeable over time. Evaluation of transport projects is a complex and difficult task, but also crucial for a company’s success in the market. We assume that certain relations of the system elements are functions of time, and thus we apply a dynamic approach – dynamic priorities in multi-criteria decision making. The topic of this paper is time dependent multi-criteria decision making in a transport projects evaluation. The model is tested on real data from the Serbian railway network. http://dx.doi.org/10.13033/ijahp.v7i1.292

Two-phase model for multi-criteria project ranking: Serbian Railways case study

An original two-phase model for ranking railway projects from different railway subsystems is presented. The model was developed for the purpose of ranking 75 Serbian Railways projects. The advantage of this model over existing one-phase models is that it allows for one to obtain not only a unique ranking list of all of the projects but also ranking lists for individual project clusters. The second essential advantage is that the application of this model eliminates the shortcoming of some of the high-ranked projects on the unique ranking list not being high-ranked on the cluster ranking list. Due to the frequency of situations in which projects contain a dualism of interests (e.g., local-global, individual-general, regional-national and national-European), based on the proposed model, a universal model for a two-phase ranking of projects was developed. The algorithm of the new model is presented herein.

The missing component in rail charging modeling—access charges principle selection

AbstractThe motive of this research is the fact that until now no universal model of access charges (AC) has been defined. In the process of modeling, the AC principle is one of the key elements for defining the AC. In this paper, a model for the AC principle selection based on the analytic network process (ANP) approach is proposed. The developed model presents the objectives of the identified stakeholders through the established criteria from three different perspectives: the government influence, railway market environment, and efficiency of network use. Based on the results of a research, network structure of the ANP method can successfully resolve the dependence and conflicts among evaluation criteria for the AC principle selection. The proposed ANP‐based model can become a tool for evaluation and ranking of the AC principle as shown in the case study of the Serbian Railways. This paper is based on real data.

A systems approach to access charges in unbundling railways

This article presents a systems approach to access charges in unbundling railways where an infrastructure manager charges services to operators on an open market. The motive for this research is the fact that until now no universal model of access charges has been defined. We define a universal access charges model for an essential service package for a mid- and small-size network based on a systems approach to recovering the costs that are incurred as a result of the operation of a train. System elements are a railway network, trains and costs. Having in mind the system complexity a combination of an analytical and engineering approach has been used for access charges modelling. The model has been developed for a Serbian mid-size railway network and tested on real data. The numerical results of model application indicate that with charges defined in this way it is possible to track cost and cost management by services.

Application of the Prediction Model "SCHALL 03" for Railway Noise Calculation in Serbia

Application of the prediction models for railway noise indicators calculation, which was already developed by other countries, represents a major challenge in Serbia. Prediction model "Schall 03" was developed in line with technical and technological characteristics of the rolling stock and infrastructure of German Railways. Prior to its application at the national level, due to different technical-technological characteristics of railway stock and railway infrastructure it is necessary to perform its validation and, depending on the needs, the calibration in accordance with local conditions. This will assure accuracy and precision of the calculations of noise indicators, as well as confidence in the results obtained by prediction model "Schall 03". This paper presents the analysis of the possibilities to apply German prediction model "Schall 03" on the Serbian railway network, more precisely railway section from Belgrade to Romanian border. Calculated values of noise indicators were compared with the results of measurements of noise indicators within measuring interval, which correspond to the referent time intervals for different day periods.

Decision support model for prioritizing railway level crossings for safety improvements: Application of the adaptive neuro-fuzzy system

Every year, more than 400 people are killed in over 1.200 accidents at road-rail level crossings in the European Union (European Railway Agency, 2011). Together with tunnels and specific road black spots, level crossings have been identified as being a particular weak point in road infrastructure, seriously jeopardizing road safety. In the case of railway transport, level crossings can represent as much as 29% of all fatalities caused by railway operations. In Serbia there are approximately 2.350 public railway level crossings (RLC) across the country, protected either passively (64%) or by active systems (25%). Passive crossings provide only a stationary sign warning of the possibility of trains crossing. Active systems, by contrast, activate automatic warning devices (i.e., flashing lights, bells, barriers, etc.) as a train approaches. Securing a level crossing (whether it has an active or passive system of protection) is a material expenditure, and having in mind that Serbian Railways is a public company directly financed from the budget of the Republic of Serbia, it cannot be expected that all unsecured level crossings be part of a programme of securing them. The most common choice of which level crossings to secure is based on media and society pressure, and on the possible consequences of a rise in the number of traffic accidents at the level crossings. The process of selecting a level crossing where safety equipment will be installed is accompanied by a greater or lesser degree of uncertainty of the essential criteria for making a relevant decision. In order to exploit these uncertainties and ambiguities, fuzzy logic is used in this paper. Here also, modeling of the Adaptive Neuro Fuzzy Inference System (ANFIS) is presented, which supports the process of selecting which level crossings should receive an investment of safety equipment. The ANFIS model is a trained set of data which is obtained using a method of fuzzy multi-criteria decision making and fuzzy clustering techniques. 20 experts in road and rail traffic safety at railway level crossings took part in the study. The ANFIS model was trained with the experiential knowledge of these experts and tested on a selection of rail crossings in the Belgrade area regarding an investment of safety equipment. The ANFIS model was tested on 88 level crossings and a comparison was made between the data set it produced and the data set obtained on the basis of predictions made by experts.

FUZZY RENEWAL THEORY ABOUT FORECASTING MISTAKES DONE BY A LOCOMOTIVE DRIVER: A SERBIAN RAILWAY CASE STUDY

The human factor is one of the most dominant causes of railway accidents. For example, human impact appears to be the main reason for 44% of railway accidents in the Republic of Serbia. Thus, a remarkable effort is undertaken to investigate human factors. Therefore, plenty of researchers have analyzed a human influence on railway accidents. This paper develops a model for forecasting the number of railway accidents caused by the human factor. The proposed model is based on the renewal theory and assumes that working time between the faults of a locomotive driver has exponential distribution (or another Erlang distribution of a higher order) characterized by parameter λ that is treated as a fuzzy dependant variable and considered as a function of job complexity, the exposure of locomotive drivers (i.e. time spent in driving) and a tendency of locomotive drivers to make mistakes. The application of the model to the population of 777 Serbian railway locomotive drivers provided encouraging results in predicting the number of railway accidents.

Modeling thermal effects in braking systems of railway vehicles

The modeling of thermal effects has become increasingly important in product design in different transport means, road vehicles, airplanes, railway vehicles, and so forth. The thermal analysis is a very important stage in the study of braking systems, especially of railway vehicles, where it is necessary to brake huge masses, because the thermal load of a braked railway wheel prevails compared to other types of loads. In the braking phase, kinetic energy transforms into thermal energy resulting in intense heating and high temperature states of railway wheels. Thus induced thermal loads determine thermomechanical behavior of the structure of railway wheels. In cases of thermal overloads, which mainly occur as a result of long-term braking on down-grade railroads, the generation of stresses and deformations occurs, whose consequences are the appearance of cracks on the rim of a wheel and the final total wheel defect. The importance to precisely determine the temperature distribution caused by the transfer process of the heat generated during braking due to the friction on contact surfaces of the braking system makes it a challenging research task. Therefore, the thermal analysis of a block-braked solid railway wheel of a 444 class locomotive of the national railway operator Serbian Railways is processed in detail in this paper, using analytical and numerical modeling of thermal effects during long-term braking for maintaining a constant speed on a down-grade railroad.

Research of defects that are related with reliability and safety of railway transport system

Engineering of reliability and safety in transport, put in the real operating conditions, makes an important research topic worldwide. This paper explores one possibility of modelling the railway transport system from the standpoint of reliability and safety. The model enables optimization of reliability of the railway transport system by analyzing the influence of various parameters on reliability. For the reliability analysis, a Markov’s model with four states is suggested (the failureless state, the state with partial failures, the completely failed state and the blocked state). The limits of the model parameters’ values were estimated on the basis of the available literature and operational experience. For estimating the parameters in terms of allocation of reliability, an EFTES distribution process, developed for application in industrial systems, was used. The model obtained for the analysis of the defects that are related with reliability and safety was tested with operational data of “Serbian Railways”. The paper shows that the presented Markov’s model with four states models well the specifics of the railway system and presents great possibilities for basic qualitative and quantitative analysis. The model enables optimization of operation, maintenance and overhaul of the system.

A TWO‐LEVEL APPROACH TO THE PROBLEM OF RAIL FREIGHT CAR FLEET COMPOSITION

One of the main objectives for a rail company is to minimize the size of rail freight car fleet in order to reduce operating costs. The problem of rail freight car fleet composition is aimed at determining an optimal structure and size of freight car fleet in order to respond to actual transport demand. A rail company must have capabilities to respond to actual transport demand in case it wants to increase the level of competitiveness on the transport market. Therefore, it is necessary that the structure and size of rail freight car fleet correspond to the structure and size of rail transport demand. In this paper, we developed a two‐level approach to determining an optimal rail freight car fleet composition. This approach has been tested for the case of the Public Enterprise ‘Serbian Railways’ and the obtained results show the potential for a practical application of the proposed approach.

Railway noise and vibration: Current European legislation and research and measurements on Serbian railway

In this paper certain current European noise legislation, standards and research including the Physical Agents Directive, the Environmental Noise Directive 2002/49/EC and the Technical Specifications for Interoperability are summarized and their implications in terms of maintaining the track are discussed. In the Environmental Noise Directive a number of research projects investigated noise mapping. From this Directive the action plans for control of noise on the environment follow. Measurements of noise and vibrations on Serbian Railway, before and after track reconstruction, are presented at the end.