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Scientific and technical journal established by OSTU. Media registration number: ПИ № ФС77-75780 dated May 23, 2019. ISSN: 2220-4245. Subscription index in the online catalog «Subscription Press» (www.akc.ru): E28002. Subscription to the electronic version is available on the «Rucont» platform.
The journal is included in the Russian Science Citation Index and in the List of Russian Scientific Journals .

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  • V.2(34), 2018
    2-13

    Operative estimating of diesel locomotive fuel consumption with its power unit mode mathematical model

    The article discusses the possibility of determining the specific fuel consumption of diesel locomotives in operation using indirect calculation methods based on the use of these locomotive onboard systems and supplementing them with mathematical models of the operating cycle and the model for determining the composition of the exhaust gases of a diesel engine. The basic equations and algorithms proposed for the implementation of such a method of mathematical models and the results of their use are presented, the results of a comparison of simulation results and experimental data on the specific consumption of fuel of diesel locomotives TEM18DM are presented. A possible algorithm for their joint use is proposed, conclusions are made on the possible development of such a method for determining the energy efficiency of diesel locomotives without taking them out of service.
  • V.1(45), 2021
    114-122

    Analysis of the seasonal dynamics of the indicator of the amount of deviations in rail gauge geometry from the second degree standard on the infrastructure of russian railways, at the network and regional levels

    Purpose. Constructing a model for predicting a quantitative indicator of the pre-discharge state of the upper structure of the track based on a statistical analysis of the seasonal dynamics of this indicator. Forecasting involves identifying bottlenecks for timely corrective action. This approach allows you to refine the construction of algorithms of the functional risk assessment system on the infrastructure of Russian Railways for managing the technical condition of the railway track and safety and is considered as an element of digitalization of the risk assessment of traffic safety in the Railway Infrastructure Directorate. The development is carried out on the basis of accepted existing regulatory documents and classifiers of risk factors operating for the infrastructure management at Russian Railways. Methods. regression analysis, data validation, modeling based on regression analysis. Results. Dependence was identified and a forecast model of the dynamics of the number of deviations of the 2nd degree rail gauge geometry (GRK) was built based on the use of actual data from the automated system Path (APCS P) of Russian Railways. Testing of the approach was carried out on the basis of the Directorate of Infrastructure of the North Caucasus Railway. The identified dependence allows you to give a fairly accurate forecast of the state of traffic safety and the development of GRK deviations on the 2nd degree for use in practice, effective planning of material costs for planned preventive work and overhaul at linear enterprises, on a specific railway adopted for calculation and on the network of Russian Railways. Practical significance. The constructed model allows predicting the intensity of the risk factor on an objective basis of seasonal patterns, as well as the volume of control impacts on the current content of the upper track structure. The presence of such a forecast will make it possible to establish a relationship between the indicator of the dynamics of the number of deviations of the 2nd degree rail gauge geometry, including seasonal dynamics, and the risk factor, that is, the number of GRK deviations of the 3rd degree used in the risk assessment on the infrastructure. The result of this approach is the solution of a system of tasks that affect the values that reflect the level of risks, and as a result, effective management of financial flows for the maintenance of infrastructure, reduction and prevention of traffic safety incidents.