O.V. Druzhinina1, I.V. Makarenkova2, I.I. Vasilyeva3

1,2 FRС «Computer Science and Control» of RAS (Moscow, Russia)

3 Bunin Yelets State University (Yelets, Russia)

1 odruzhinina@frccsc.ru, 2 imakarenkova@frccsc.ru, 3 irinavsl@mail.ru

One of the significant areas of research is the study of dynamic models of the organizational and technological process of repairing railway transport equipment. The relevance of this area is related to the need to solve transport safety issues, develop digital twins, and improve diagnostic systems and decision support systems. It is important to note the significance of using methods such as differential equation theory, stochastic system theory and numerical methods. The stochastization of the studied models is aimed at analyzing the influence of random disturbances at various stages of the life cycle of transport system elements. The purpose of this work is to analyze two-dimensional dynamic models of the organizational and technological process of railway car repair taking into account random disturbances and various parametric dependencies. Deterministic and stochastic two-dimensional dynamic models describing organizational and technological processes in railway transport are considered. To analyze these processes, non-stationary stochastic generalizations of Lotka–Volterra models are proposed, taking into account resource–consumer interactions. The transition to systems of equations in the Langevin form has been performed. Modifications of stochastic models based on additive and multiplicative Gaussian noises have been constructed. Linear and exponential time dependencies of parameters have been considered for stochastic dynamic models. Computer experiments have been conducted using a software package in the Python language, and trajectories have been constructed for deterministic and stochastic cases. The influence of additive and multiplicative noise on trajectory dynamics is characterized and the qualitative effects of stochasticization are identified taking into account the variability of Gaussian noise intensities. The results can be useful in solving problems related to the construction of nonlinear stochastic models of technical systems and the optimization of vehicle numbers. The results can also be applied in the development of algorithmic support for digital twins and monitoring systems for transport infrastructure elements as well as in the creation and improvement of technologies for the repair and operation of vehicles, taking into account random disturbances.

Druzhinina O.V., Makarenkova I.V., Vasilyeva I.I. Analysis of stochastic models of the organizational and technological process of repairing railway equipment // Science Intensive Technologies. 2026. V. 27. № 5. P. 31−44. DOI: https://doi.org/10.18127/j19998465-202605-04

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