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The paper studies the determination for one of the dynamic quality parameter (PDK) of railway vehicles — car body lateral acceleration — by using of computer simulation system for railway vehicles dynamic Simpack Rail. This provide the complex simulation environment with variable velocity depending on the train schedule. The rail vehicle model of typical 1520 mm gauge fright locomotive section used for simulation has been verified by means of the chair “Electric multiple unit cars and locomotives” in the Russian University of Transport (RUT (MIIT)). Due to this homologation the questions of model creating and verification in preprocessor are excluded in this paper. The paper gives the detail description of cartographic track modeling in situation plane, heights plane and superelevation plane based on the real operating data. The statistic parameters (moments) for the rail related track excitation and used cartographic track data of the specified track section in this simulation are given as a numeric and graphical results of reading the prepared data files. The measurement of the car body residual lateral acceleration occur under consideration of the earth gravity acceleration part like the accelerometer measurement in the real world. Finally the desired quality parameter determined by simulation is compared with the same one given by a test drive. The calculation method in both cases is based on the middle value of the absolute maximums picked up within the nonstationary realizations of this parameter. Compared results confirm that this quality factor all the first depends on the velocity and track geometry properties. The simulation of the track in this application uses the strong conformity original track data of the test ride track section. The accepted simplification in the rail vehicle model of fright electric locomotive section (body properties related to the center of gravity, small displacements between the bodies) by keeping the geometric and force law characteristics of the force elements and constraints constant allow in Simpack Rail the simulation with necessary validity of system behavior (reactions).

This paper is dedicated to the analysis of medical and biological data obtained through locomotor training and testing of astronauts conducted both on Earth and during spaceflight. These experiments can be described as the astronaut’s movement on a treadmill according to a predefined regimen in various speed modes. During these modes, not only the speed is recorded but also a range of parameters, including heart rate, ground reaction force, and others, are collected. In order to analyze the dynamics of the astronaut’s condition over an extended period, it is necessary to perform a qualitative segmentation of their movement modes to independently assess the target metrics. This task becomes particularly relevant in the development of an autonomous life support system for astronauts that operates without direct supervision from Earth. The segmentation of target data is complicated by the presence of various anomalies, such as deviations from the predefined regimen, arbitrary and varying duration of mode transitions, hardware failures, and other factors. The paper includes a detailed review of several contemporary retrospective (offline) nonparametric methods for detecting multiple changepoints, which refer to sudden changes in the properties of the observed time series occurring at unknown moments. Special attention is given to algorithms and statistical measures that determine the homogeneity of the data and methods for detecting change points. The paper considers approaches based on dynamic programming and sliding window methods. The second part of the paper focuses on the numerical modeling of these methods using characteristic examples of experimental data, including both “simple” and “complex” speed profiles of movement. The analysis conducted allowed us to identify the preferred methods, which will be further evaluated on the complete dataset. Preference is given to methods that ensure the closeness of the markup to a reference one, potentially allow the detection of both boundaries of transient processes, as well as are robust relative to internal parameters.