Open Access
E3S Web of Conf.
Volume 402, 2023
International Scientific Siberian Transport Forum - TransSiberia 2023
Article Number 12011
Number of page(s) 11
Section Geotechnical Engineering, Road and Bridge Construction
Published online 19 July 2023
  1. Kosenko, S., Akimov, S.: Design of track structure for corridors of heavy-train traffic. MATEC Web Conf. 239, 1–12 (2018). Article No. 05005. [Google Scholar]
  2. Kosenko, S., Akimov S., Surovin P. Technology of rail replacement at end stresses. MATEC: Web of Conferences. Volume 216, pp 1–8 (2018). [Google Scholar]
  3. Kosenko, S. A., Akimov S.S. Performance characteristics of differentially quenched. Magazine of Civil Engineering. Volume 7, pp 94-105 (2017). [Google Scholar]
  4. Victor Kochergin, Igor Maksimov, Victor Pevzner and Evgeniya Polunina. Track loading on Russian Railways under modern maintenance conditions. E3S Web Conf. Volume 135, Article 02002 [Google Scholar]
  5. Victor Pevzner, Valerii Kaplin. Improving the Railway Stability in the Joint Zone for Modern Operating Conditions. Transportation Research Procedia. Volume 54, pp 328-333 (2021). [CrossRef] [Google Scholar]
  6. Weston P., Roberts C., Yeo G, Stewart E. Perspectives on railway track geometry condition monitoring from in-service railway vehicles. Vehicle System Dynamics. Volume 53, pp 1063-1091 (2015). [CrossRef] [Google Scholar]
  7. Kasraei, Ahmad , Zakeri, Jabbar Ali. Effective time interval for railway track geometry inspection. Archives of Transport. 2020. Volume 53, issue 1, pp 53—65 (2020). [Google Scholar]
  8. Khajehei H, Ahmadi A., Soleimanmeigouni I., Nissen A. Allocation of effective maintenance limit fir railway track geometry. Structure and Infrastructure Engineering. 2019. Volume 15, pp 1597-1612 (2019). [CrossRef] [Google Scholar]
  9. Guler H., Jovfnovic S., Evren G. Modelling railway track geometry deterioration. Proceedings of the Institution of Civil Engineers. Volume 164. Issue 2, pp 65-75 (2011). [CrossRef] [Google Scholar]
  10. Sadeghi J. Development of Railway Track Geometry Indexes Based on Statistical Distribution of Geometry Data. Journal of Transportation Engineering. Volume 136. p. 693-700 (2010). [CrossRef] [Google Scholar]
  11. Guler H. Prediction of railway track geometry deteriorationusing artificial neural networks: A case study for Turkish state. Structure and Infrastructure Engineering. Volume 10, Issue 5, pp 614-626 (2014). [CrossRef] [Google Scholar]
  12. Sadeghi J., Askarinejad H. Application of neural networks in evaluation of railway track quality condition. Journal of mechanical science and technology. Volume 26, Issue 1, pp 113-122 (2012). [CrossRef] [Google Scholar]
  13. Kasraei A., Zakeri J., Bakhtiary A. Optimal track geometry maintenance limits using machine learning: A case study. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. Volume 235, Issue 7, pp 876-886 (2020). [Google Scholar]
  14. A. Ivanova, A. Butsanets, V. Breskich, T. Zhilkina, Autonomous Shipping Means: the Main Areas of Patenting Research and Development Results, Transportation Research Procedia, Volume 54, 2021, Pages 793-801, [CrossRef] [Google Scholar]
  15. Jens C., Nielsen O., Li X. Railway track geometry degradation due to differential settlement of ballast/subgrade – Numerical prediction by an iterative procedure. Jornak of Sound and Vibration. Volume 412, pp 441-456 (2018). [CrossRef] [Google Scholar]
  16. Pevzner V.O., Nadezhin S.S., Anisin A.V., Tretyakov I.V. Assessment of railway track deformability at the sites of its deterioration and of possible changes in track alignment time specifications due to increase in freight car axle-loads. JSC Railway Research Institute (JSC VNIIZhT). Volume 4, pp 44-48 (2013). [Google Scholar]

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