Institution
Dnipropetrovsk National University of Railway Transport named after Academician V. Lazaryan
Education•Dnipro, Ukraine•
About: Dnipropetrovsk National University of Railway Transport named after Academician V. Lazaryan is a education organization based out in Dnipro, Ukraine. It is known for research contribution in the topics: Track (rail transport) & Bogie. The organization has 736 authors who have published 655 publications receiving 1468 citations. The organization is also known as: Institute of Railway Transport Engineers.
Topics: Track (rail transport), Bogie, Train, Traction substation, Voltage
Papers published on a yearly basis
Papers
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01 Jan 2005-Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport
TL;DR: In this article, factors have been examined that influence the strength parameters and other characteristics of railway wheels, such as the number of wheels and the type of wheels used for locomotion.
Abstract: Factors have been examined that influence the strength parameters and other characteristics of railway wheels.
1 citations
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25 Apr 2004-Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport
TL;DR: This system allows us to control and measured the parameters of code current of automatic locomotive signaling system and to define spectral composition of traction current.
Abstract: In this paper the results of elaboration of automated microprocessor system are given. This system allows us to control and measured the parameters of code current of automatic locomotive signaling system and to define spectral composition of traction current. It can be used on the basis of car-laboratory or at the measurements on the railway section.
1 citations
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01 Jan 2009-Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport
TL;DR: In this paper, a computer-aided simulation model is presented that can be used for the research of the railway traffic organization and also for the estimation of influence of the train parameters on the operation indices of railway lines and directions.
Abstract: The computer-aided simulation model is offered that can be used for the research of the railway traffic organization and also for the estimation of influence of the train parameters on the operation indices of railway lines and directions.
1 citations
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24 Dec 2015-Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport
TL;DR: In this paper, the authors developed a method to estimate the errors of determination the interaxle distance of the flexible units in the control section using the point path-control transducer for future identification of cars and locomotives.
Abstract: Purpose . The identification of rolling stock on the railroads is an integral part of many automation systems as trains in general and cars separately. Various information management systems at sorting yards require the operational information about the object while performing the manufacturing operations. The improvement of the determination accuracy of different parameters characterizing the rolling stock, leads to the immediate quality progress in the traffic volumes management. The aim of the paper is to develop a method to estimate the errors of determination the interaxle distance of the flexible units in the control section using the point path-control transducer for future identification of cars and locomotives. Methodology . To achieve this goal the simulation method and experiment planning were used. The simulation model allowing determining the time intervals between the collisions of wheelset of movable units in point path-control transducer on the control section with variable characteristics of identification devices was developed. The values of the time intervals obtained with using the simulation mode were applied in the method of experiment planning to the final target. Findings . The calculated analytical values of the errors of the interaxle distances do not have the significant differences from values obtained using the simulation model. It makes possible to use the received functional dependence to estimate the possible errors in the identification of rolling stock. The results of this work can be used to identify separate flexible units, and trains in general. Originality . The functional dependence of the error of the interaxle distance error from the fixing point of the wheel path-control transducer, the distance between the sensors and the measured distance was derived using a previously conducted research of the factors influencing the error in determining the interaxle distance of the movable units, and developed simulation model to calculate the interaxle distance. Practical value. This functional dependence allows solving the following tasks: to calculate the maximum possible error of determining the interaxle distance of the movable units at known parameters of control section and calculation of parameters of the control section, when the possible acceptable error of determining the interaxle distance of the flexible units is known.
1 citations
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01 Jan 2008-Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport
TL;DR: In this article, the authors propose an approach to improve the quality of the information provided by the users by using the information of the user's interaction with the service provider, such as:
Abstract: В статье рассматривается постановка задачи определения продолжительности зон H –характеристики с учетом свойств функции среднего числа отказов и функции интенсивности отказов. Постановка задачи сформулирована как задача на определение структуры.
1 citations
Authors
Showing all 739 results
Name | H-index | Papers | Citations |
---|---|---|---|
Vitalii Kovalchuk | 9 | 49 | 284 |
Serhiy V. Myamlin | 8 | 36 | 203 |
Larysa O. Neduzha | 7 | 24 | 153 |
Roman V. Vernigora | 6 | 11 | 79 |
Dmytro M. Kozachenko | 6 | 28 | 112 |
D. M. Kurhan | 6 | 23 | 103 |
Valeriy Kuznetsov | 5 | 27 | 67 |
Eugene O. Voronkov | 5 | 13 | 72 |
A. O. Shvets | 5 | 8 | 32 |
A. O. Shvets | 5 | 6 | 50 |
V. I. Shynkarenko | 4 | 26 | 81 |
Tetyana Kolesnykova | 4 | 6 | 27 |
Volodymyr I. Bobrovskyi | 4 | 6 | 44 |
E. Ph. Shtapenko | 4 | 12 | 32 |
Mykola M. Biliaiev | 4 | 49 | 54 |