| Issue |
E3S Web Conf.
Volume 627, 2025
VI International Conference on Geotechnology, Mining and Rational Use of Natural Resources (GEOTECH-2025)
|
|
|---|---|---|
| Article Number | 04014 | |
| Number of page(s) | 8 | |
| Section | Automation, Digital Transformation and Intellectualization for the Sustainable Development of Mining and Transport Systems, Energy Complexes and Mechanical Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202562704014 | |
| Published online | 16 May 2025 | |
Algorithm for the calculation of the load capacity of the equipment of reverse traction networks
1 Joint Stock Company Railway Research Institute, 10, 3rd Mytishchinskaya St., Moscow, 129626, Russia
2 Ural State University of Railway Transport, 66, Kolmogorova St., Ekaterinburg, 620034, Russia
* Corresponding author: Kharkovskaya.Elena@vniizht.ru
The rapid expansion of freight traffic on Russia’s Eastern polygon has necessitated significant infrastructure upgrades by JSCO "RZD". This paper presents a novel software module developed by JSC “VNIIZHT” for analyzing the load capacity of reverse traction rail network devices. Integrated into the System for planning, rationing and analyzing the use of fuel and energy resources for train traction, this module addresses a critical gap in the company’s technological capabilities. The software employs a two-stage approach: first, constructing and calculating an instantaneous substitution scheme of the design section, and second, determining the load capacity of reverse traction rail network devices based on specified traffic schedules. This innovative tool enables multi-variant calculations, allowing specialists to make informed decisions on technical solutions, potentially reducing operating costs and optimizing infrastructure investments. The module’s outputs provide valuable insights into the capacity of reverse traction rail network devices under various operational conditions, contributing to more efficient and cost-effective railroad electrification systems.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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