This paper presents a method for the non-contact determination of the adiabatic wall temperature in high-speed gas flows. The method is based on the processing of a sequence of thermograms obtained using an IR camera, within a program developed in Python 3.10. The approach demonstrated high efficiency when handling large datasets, particularly concerning minimizing temporal and computational demands. The adiabatic wall temperature was determined under both steady-state conditions, directly in the experiment, and transient conditions, through the extrapolation of the heat flux as a function of the current temperature of the examined surface. The effectiveness of this method was demonstrated in the investigation of non-mechanical energy separation in compressible gas flows.

The paper considers the foreign experience of teaching engineering students to analyze speech signals using instrumental methods. Examples of obtaining spectrograms are given, as well as the capabilities of speech analysis software used in undergraduate and graduate engineering courses at the University of California (Los Angeles, USA). The disadvantages of speech analysis and visualization based on Fourier transform are shown. New solutions for processing and visualizing speech signals based on multilevel wavelet analysis are proposed. The main characteristics of the developed WaveView and WaveView-MWA programs that provide increased time-frequency resolution of vowel sounds are considered. For the first time, the results of high-precision analysis and visualization of consonant sounds - non-stationary signals inaccessible to spectral analysis using the Fourier transform are presented. A comparative analysis of the time-frequency resolution of spectrograms and wavelet sonograms in the visualization of English speech is performed. The developed technology of high-precision analysis and visualization of speech signals is used in the training of specialists of the Department of «Information Security» of the Faculty of «Informatics and Management» of the Bauman Moscow State Technical University during laboratory work on the course «Forensic study of phonograms».

A method of searching optimal nodes of approximation realized on the example of Runge function is proposed. The method is based on the use of interpolation algebraic curves in point calculus and is reduced to minimization of the target function of many variables, which provides minimum deviations of the approximating function from the original one. Traditionally, in the process of interpolation, the coefficients of the interpolating function are determined on the basis of the initial points, which does not make it possible to ensure the search for the optimal location of interpolation nodes, since the coordinates of the node points are necessary to determine the coefficients of the interpolating function. The peculiarity of interpolation curves realized in point calculation is that they are obtained by uniform distribution of the parameter along the numerical axis and keep the coordinates of interpolation nodes in the point equation, which makes it possible to set and solve the problem of their optimal location by minimizing the target function. After the realization of the coordinate calculation of the point equation of the interpolation curve, the final result of the approximation of the original function is an algebraic curve given in parametric form, which allows us to use the nonlinearity of space to significantly reduce the degree of the approximating polynomial function. For example, when using Chebyshev nodes, which are considered optimal for approximating the Runge function, at least 20 nodes are needed to achieve a high-quality approximation, which leads to the need to use a polynomial of degree 19. In this case, the MSE is 0.000111. Whereas for the Runge function approximation based on the optimized arrangement of approximation nodes, even when using 6 node points, the MSE is only 0.0000284, which is an order of magnitude lower compared to Chebyshev nodes and allows using two polynomials of degree 5 on each of the coordinate axes instead of one polynomial of degree 19.

The results of an experimental study of an air-droplet flow in a flat supersonic Laval nozzle of a periodic-acting wind tunnel are presented. The droplets were fed into the flow using fine spray nozzles installed in the pre-chamber. The working part of the wind tunnel has a rectangular cross-section with dimensions of 70x98 mm. The Mach number at the nozzle exit varied in the range 2,0-3,0 due to the mechanism of compression of the nozzle critical section, the total pressure in the pre–chamber was 450-550 kPa, and the total temperature was 288-298 K. The initial concentration of the dispersed (liquid) phase in the flow and the initial droplet size distribution were varied by changing the pressure drop at the spray nozzles. When studying the dynamics of droplet crushing in the critical section of the nozzle, the SSP (shadow photography) laser method was used, which includes: a flow illumination system based on a Beamtech dual-pulse Nd:YAG laser with a wavelength of 532 nm, a 7-joint optical arm for delivering laser radiation, a light-scattering screen for creating a backlight with alcohol solution of rhodamine phosphor, a digital CCD camera with a frame rate at full resolution up to 15 Hz, an Infinity K2 DistaMax microscope lens and the synchronization processor. A series of snapshots of the instantaneous state of the air-droplet flow in the critical section and in the expanding part of the Laval nozzle were obtained.

The technologies of artificial intelligence and machine learning have made a fundamental leap in their capabilities in the last five years. The growth of processing power and the emergence of more and more effective methods of machine learning allows AI to not just solve the most typical tasks associated with the field, such as statistical analysis and optimization of mathematical processes, but also to find new applications in related fields of research, as well as practical applications, including those on the free market, available to the mass consumer. Image generation, audio, animation, self-learning models of control of robotic platforms and virtual mechanical models – these and many more novel applications of the recent years have led to a media-boom around AI and a growing interest from developers and authors from various fields and industries. That being said, the methods for developing, research, testing, and integration of AI have largely remained unchanged and still require the knowledge of programming languages, machine learning libraries, as well as a deep understanding and experience specifically in the narrow field of AI. This barrier of specialization not only demands inclusion of machine learning specialists in the development process of otherwise trivial computer applications, typical for the field of AI, but also prevents small teams and independent developers from using the latest advances in these technologies without significant monetary and time investments into studying the subject. I offer a novel solution to this issue in the form of a prototype graphical interface that allows the user without technical education and without the need for knowledge of programming languages to develop and tune various architectures of neural nets and other machine learning methods, methods of unsupervised machine learning, and to test these methods on a wide range of experimental tasks – from mathematical equations to controlling virtual mechanical models in a simulated physical environment. In this article, I give a brief description of its structure and organisation, its fundamental principles of operation, and the capabilities of this GUI.

The paper presents the results of using Evercam F 1000-16-C high-speed cameras for high-speed visualization of laser initiation and high-temperature combustion of Al-CuO thermite mixture. The possibility of determining process parameters based on the results of high-speed shooting is demonstrated. Two visualization modes are considered: synchronous operation of two cameras to obtain images from two angles, and synchronous operation of two cameras as part of a laser monitor with a copper bromide vapor brightness amplifier. In the case of direct video recording, one of the cameras acts as the master one, and the recording frequency is set in the service program. It is proposed to use a two-angle video recording mode to study the spread of flame in a volume. For the first time, Evercam F 1000-16-C cameras were used as part of a laser monitor with a copper bromide vapor brightness amplifier. Laser monitoring, combined with direct video recording, makes it possible to study the surface of a sample in the area of igniting laser interaction and flame propagation in one of the planes. A feature of the operation of Evercam cameras as part of a laser monitor is the need to generate trains of clock pulses synchronized with the radiation pulses of the brightness amplifier and the radiation pulse of the igniting laser. In this case, both cameras work in slave mode. The synchronization unit is designed using the STM32F103C8T6 microcontroller board and has galvanically isolated input and output signals.

The paper describes methods and approaches for imitation of optical effects when rendering images from models of various surveillance device in a three-dimensional virtual environment. This allows for the possibility expansion of such modeling by ensuring coverage of a wide range of real devices as prototypes for the virtual analogues being created. An original approach to two-stage image synthesis with radial distortion implementation is proposed, as well as methods and algorithms for simulation of lateral and longitudinal chromatic aberrations. Developed solutions are based on the use of modern multi-core graphics processing units and shader rendering technology. They provide visualization of video streams from simulated surveillance devices in real time. Software modules were created based on developed methods and approaches. Approbation of them was carried out in virtual environment system VirSim [1] and showed adequacy and effectiveness of proposed solutions when using in virtual environment systems and training complexes.

The subject of the study is the construction and application of visual models using the concept of visualization metaphors in the context of exploratory analysis of heterogeneous data. This study considers improved variants of the previously proposed visualization metaphors that can be used as a basis for building visual models. A technology for exploratory analysis of heterogeneous data based on the joint use of different visualization metaphors is proposed. The process of visual data exploration at the stage of exploratory analysis using the proposed technology is demonstrated to be iterative and multiscenary, contingent upon the analysis goals. The software tool developed to implement the proposed technology is described, along with its additional functionality to calculate and export quantitative characteristics of the visual model. The software tool is then considered in the context of exploratory analysis of a synthetic data set. The future direction of the proposed approach to the construction of visual models, the technology of exploratory data analysis and the software tool for its support are determined.

First of all the paper considers the problem of verification or formalization of the online visualization and parallel computing system from the point of view of dynamic systems as a development of the theory of computational complexity for random processes. Considering problems involving truly big data inevitably leads to the use of a block approach which is also used in both information theory and stochastic differential equations. As a natural metaphor the graph signals were chosen. This is a graph in nodes, of which a spectral function is defined in the examples considered this is a function of color (RGB), height or amount of data. In parallel computing, a block can be associated with a computing unit (processor) and consider the problem of entropy (performance) maximization. In the developed on-line visualization and concurrent computing system for geometric parallelization, it is possible to implement and compare a stationary random process (equiprobable messages implemented using broadcasting and mixins) and a steady-state random process (point-to-point messages), which have different analytical solutions. Together, this allows concluding that the proposed implementation of a stationary process has a certain novelty; in addition, it was intended to be more convenient for automated parallelization. The problems of automatic load balancing (interpolation problem) and optimal scalability of parallel computing (extrapolation problem) are also considered. Not much has been done in the field of visualization verification for example a mesh visualization has been proposed to be considered as a parameterized model of a white-noise random process. Of course, this work cannot be considered complete, but the direction that the authors called stochastic semantics is obviously promising. The authors intend to take a close look at the established perturbed processes in the field of visualizations including those that take into account the human factor (the sketches of the formalization in the form of a discussion are given).

For two-dimensional Euler equations, flow control using spatially distributed stationary heat sources is considered. The initial flow, characterized by the interaction of Edney - type shock waves, was changed with the help of heat sources in such a way as to reduce the maximum pressure on the surface of the body. The problem was solved in an optimization formulation using conjugate equations to calculate the gradient of the target functional. In addition to visualizing flow parameters in this problem, it is of interest to visualize the distribution of adjoint parameters and heat sources.