Факультет прикладних комп'ютерних технологій (ДМетІ) <br> Дніпровський металургійний інститут (ДМетІ)

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UK: Факультет прикладних комп'ютерних технологій (ДМетІ)
Дніпровський металургійний інститут (ДМетІ) EN: Faculty of Applied Computer Technology
Dnipro Metallurgical Institute

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Aircraft Detection with Deep Neural Networks and Contour-Based Methods
(National University "Zaporizhzhia Polytechnic", Zaporizhzhia, 2024) Radionov, Y. D.; Kashtan, Vita Yu.; Hnatushenko, Volodymyr V.; Kazymyrenko, O. V.
ENG: Context. Aircraft detection is an essential task in the military, as fast and accurate aircraft identification allows for timely response to potential threats, effective airspace control, and national security. The use of deep neural networks improves the accuracy of aircraft recognition, which is essential for modern defense and airspace monitoring needs. Objective. The work aims to improve the accuracy of aircraft recognition in high-resolution optical satellite imagery by using deep neural networks and a method of sequential boundary traversal to detect object contours. Method. A method for improving the accuracy of aircraft detection on high-resolution satellite images is proposed. The first stage involves collecting data from the HRPlanesv2 dataset containing high-precision satellite images with aircraft annotations. The second stage consists of preprocessing the images using a sequential boundary detection method to detect object contours. In the third stage, training data is created by integrating the obtained contours with the original HRPlanesv2 images. In the fourth stage, the YOLOv8m object detection model is trained separately on the original HRPlanesv2 dataset and the dataset with the applied preprocessing, which allows the evaluation of the impact of additional processed features on the model performance. Results. Software that implements the proposed method was developed. Testing was conducted on the primary data before preprocessing and the data after its application. The results confirmed the superiority of the proposed method over classical approaches, providing higher aircraft recognition accuracy. The mAP50 index reached 0.994, and the mAP50-95 index reached 0.864, 1% and 4.8% higher than the standard approach. Conclusions. The experiments confirm the effectiveness of the proposed method of aircraft detection using deep neural networks and the process of sequential boundary traversal to detect object contours. The results indicate this approach’s high accuracy and efficiency, which allows us to recommend it for use in research related to aircraft recognition in high-resolution images. Further research could focus on improving image preprocessing methods and developing object recognition technologies in machine learning.
Analysis and Research of the Causes and Course of Degradation of Lithium Batteries
(EDP Sciences-Web of conferences, 2024) Buriak, Serhii Yu.; Gololobova, Oksana O.; Havryliuk, Volodymyr I.; Serdiuk, Tetiana M.; Voznyak, Oleh M.; Manachyn, Ivan O.
ENG: Energy storage devices based on lithium technology are confidently leading the respective market due to their significant advantages over other technologies in the industry. Despite their relatively recent history of appearance, they managed to undergo many modifications of both physical and chemical components. One of the constant goals of all research in this field is the formation of knowledge about the degradation processes occurring inside a given chemical current source, and ways to influence them. Systematization and identification of the fundamental reasons for the decrease in the performance of lithium batteries still remains a topical issue of today, and therefore is considered in this article. And no matter how studied this issue looks, taking into account the existing many long-term experimental data of a huge number of scientists and a number of different types of companies, but still, optimization of work is impossible without identifying and eliminating as many destructive factors as possible in battery operation. The difficulty of this process lies also in the fact that, taking into account all the high-tech production processes in the world, there are no two identical lithium current sources. On the example of a single battery, the ability to maintain high performance, close to nominal, was demonstrated from a source that, due to its lifetime, should not have had them. The data obtained during the experiment, which confirmed the high performance, show once again that the issue of degradation of lithium current sources can and should be studied further.
Analysis of Air Dust Pollution in the Transport Compartment of the Launch Vehicle at the Stage of the Pre-launch Preparation
(Printing House “Technologija”, Kaunas, Lithuania, 2024) Biliaiev, Mykola M.; Biliaieva, Viktoriia V.; Kozachyna, Vitalii A.; Kozachyna, Valeriia V.; Mashykhina, Polina B.; Semenenko, Pavlo
ENG: At the stage of the pre-launch preparation, it is necessary to fulfill very strict environment conditions inside the main fairing where the satellite is located. Namely, it is very important to predict dust concentration inside the main fairing and especially near satellite surface during forced ventilation. To predict air dust pollution inside of main fairing 2D fluid dynamics numerical model has been developed. The governing equations include equation of potential flow to simulate air flow inside the main fairing and equation of pollutant dispersion. Also, empirical model has been used to calculate the number of dust particles fall to the satellite surface. Implicit finite difference schemes of splitting have been used for numerical integration of governing equations. The computer code has been developed on the basis of proposed numerical model. The results of computational experiments to estimate dust concentration field inside the main fairing of the launch vehicle are presented.
Analysis of Changes in Global Warming Potential during Enrichment and Production of Battery-Grade Graphite Using Electrothermal Fluidized Bed Technology
(IOP Publishing Ltd, 2024) Hubynskyi, Semen M.; Sybir, Artem; Fedorov, Serhii S.; Usenko, Andrii Yu.; Hubynskyi, Mykhailo V.; Vvedenska, Tetyana
ENG: The greenhouse gas emissions during the production of anode class graphite for the conditions of Ukraine have been calculated. Conventional technologies and technologies using electrothermal fluidized bed (EFB) for natural and synthetic graphite have been studied. Calculations are carried out with respect to the whole technological chain, starting from extraction and processing of raw materials and ending with finishing processing (coating). As a result, it is shown that the technology of using EFB for purification of natural graphite and graphitization of synthetic graphite is competitive in terms of global warming potential (GWP). In the production of natural graphite using thermal purification with EFB instead of chemical purification, emissions of greenhouse gases practically remain at the same level. At the same time, the use of acids is eliminated, and the environmental impact associated with them is reduced. Production of synthetic graphite of anodic quality in EFB furnaces allows to reduce greenhouse gases (GHG) emissions by 40-50% in comparison with traditional graphitization technologies in Acheson and Kastner furnaces. The effect is achieved by reducing energy and raw material consumption.
Analysis of Methodologies for Carbon Stock Estimation in Forests
(Український державний університет науки і технологій, ННІ «Інститут промислових та бізнес технологій», ІВК «Системні технології», Дніпро, 2022) Kavats, Olena O.; Khramov, Dmitriy A.; Sergieeiva, Kateryna L.; Vasyliev, Volodymyr V.
ENG: Current approaches to carbon stock estimation in forest ecosystems are discussed. Datasets containing biomass and carbon stock estimates that can be used for training/validation in machine learning are described. Examples of applying the remote approach to assessing forest biomass over large areas are analyzed. To estimate the forest carbon stocks in Ukraine, the most promising is the remote approach, which combines ground-based and satellite measurements for forest classification and statistical modeling of carbon stocks. For training and validation of machine learning algorithms, it is proposed to use the GEDI Biomass Map covering most of the territory of Ukraine — from the southern borders to the latitude of Chernihiv in the north. A prototype of forest biomass estimating product in Ukraine can be based on publicly available MODIS NBAR data, SRTM DEM, ECMWF climate data and use the Random Forest machine learning method.
Analysis of Monolithic and Microservice Architectures Features and Metrics
(Хмельницький національний університет, Україна, 2021) Selivorstova, Tatjana V.; Klishch, Sergey M.; Kyrychenko, Serhii; Guda, Anton I.; Ostrovskaya, Kateryna Yu.
ENG: In this paper the information technologies stack is presented. These technologies are used during network architecture deployment. The analysis of technological advantages and drawbacks under investigation for monolithic and network architectures will be useful during of cyber security analysis in telecom networks. The analysis of the main numeric characteristics was carried out with the aid of Kubectl. The results of a series of numerical experiments on the evaluation of the response speed to requests and the fault tolerance are presented. The characteristics of the of monolithic and microservice-based architectures scalability are under investigation. For the time series sets, which characterize the network server load, the value of the Hurst exponent was calculated. The research main goal is the monolithic and microservice architecture main characteristics analysis, time series data from the network server accruing, and their statistical analysis. The methodology of Kubernetes clusters deploying using Minikube, Kubectl, Docker has been used. Application deploy on AWS ECS virtual machine with monolithic architecture and on the Kubernetes cluster (AWS EKS) were conducted. The investigation results gives us the confirmation, that the microservices architecture would be more fault tolerance and flexible in comparison with the monolithic architecture. Time series fractal analysis on the server equipment load showed the presence of long-term dependency, so that we can treat the traffic implementation as a self-similar process. The scientific novelty of the article lies in the application of fractal analysis to real time series: use of the kernel in user space, kernel latency, RAM usage, caching of RAM collected over 6 months with a step of 10 seconds, establishing a long-term dependence of time series data. The practical significance of the research is methodology creation of the monolithic and microservice architectures deployment and exploitation, as well as the use of time series fractal analysis for the network equipment load exploration.
Application of Biomass Pellets for Iron Ore Sintering
(Trans Tech Publications Ltd, Switzerland, 2021) Kieush, Lina; Koveria, Andrii; Qiao Zhu, Zuo; Boyko, Maksym M.; Sova, Artem; Yefimenko, Vadym
ENG: Purpose. The use of biomass as fuel might solve several technological and environmental issues and overcome certain challenges of sinter production. In particular, as revealed by comprehensive analyses, biomass can be used as fuel for iron ore sintering. In this study, we investigate the use of some raw and pyrolysis-processed biomass pellet types, namely wood, sunflower husks (SFH), and straw, for iron ore sintering. In the experiments, the pyrolysis temperature was set to 673, 873, 1073, and 1273 K, and the proportion of biomass in the fuel composition was set to 25%. It was established that the addition of biofuels to the sintering blend leads to an increase in the gas permeability of the sintered layer. The analysis of the complex characteristics of the sintering process and the sinter strength showed the high potential of wood and sunflower husk pellets pyrolyzed at 1073 and 873 K, respectively, for iron ore sintering. The analysis of the macrostructure of the sinter samples obtained using biomaterials revealed that with higher pyrolysis temperatures; the materials tend to have greater sizes and higher amounts of pores and cracks. The composition analyses of the resultant sinters revealed that with higher temperature, the FeO content of the sinters tends to increase.
Application of Neural Networks for Prediction Financial Time Series
(Scientific Publishing Center “Sci-conf.com.ua”, Perfect Publishing, 2024) Prokofiev, Taras; Ostrovska, Kateryna Yu.
ENG: The article discusses some aspects and features of the use of neural networks for forecasting financial time series for the purpose of making a profit. The use of neural networks to analyze financial information is a promising alternative (or complement) to traditional research methods. Due to their adaptability, the same neural networks can be used to analyze several instruments and markets, while the patterns found by a player for a specific instrument using technical analysis methods may work worse or not work at all for other instruments.
Application of Two-Dimensional Padé-Type Approximations for Image Processing
(National University «Zaporizhzhia Polytechnic», Zaporizhzhia, 2023) Olevskyi, V. I.; Hnatushenko, Volodymyr V.; Korotenko, G. M.; Olevska, Yu. B.; Obydennyi, Ye. O.
ENG: Context. The Gibbs phenomenon introduces significant distortions for most popular 2D graphics standards because they use a finite sum of harmonics when image processing by expansion of the signal into a two-dimensional Fourier series is used in order to reduce the size of the graphical file. Thus, the reduction of this phenomenon is a very important problem. Objective. The aim of the current work is the application of two-dimensional Padé-type approximations with the aim of elimination of the Gibbs phenomenon in image processing and reduction of the size of the resulting image file. Method. We use the two-dimensional Padé-type approximants method which we have developed earlier to reduce the Gibbs phenomenon for the harmonic two-dimensional Fourier series. A definition of a Padé-type functional is proposed. For this purpose, we use the generalized two-dimensional Padé approximation proposed by Chisholm when the range of the frequency values on the integer grid is selected according to the Vavilov method. The proposed scheme makes it possible to determine a set of series coefficients necessary and sufficient for construction of a Padé-type approximation with a given structure of the numerator and denominator. We consider some examples of Padé approximants application to simple discontinuous template functions for both formulaic and discrete representation. Results. The study gives us an opportunity to make some conclusions about practical usage of the Padé-type approximation and about its advantages. They demonstrate effective elimination of distortions inherent to Gibbs phenomena for the Padé-type approximant. It is well seen that Padé-type approximant is significantly more visually appropriate than Fourier one. Application of the Padé-type approximation also leads to sufficient decrease of approximants’ parameter number without the loss of precision. Conclusions. The applicability of the technique and the possibility of its application to improve the accuracy of calculations are demonstrated. The study gives us an opportunity to make conclusions about the advantages of the Padé-type approximation practical usage.
Automated Building Damage Detection on Digital Imagery Using Machine Learning
(Dnipro University of Technology, Ukraine, 2023) Kashtan, Vita Yu.; Hnatushenko, Volodymyr V.
ENG: Purpose. To develop an automated method based on machine learning for accurate detection of features of a damaged building on digital imagery. Methodology. This article presents an approach that employs a combination of unsupervised machine learning techniques, specifically Principal Component Analysis (PCA), K-means clustering, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), to identify building damage resulting from military conflicts. The PCA method is utilized to identify principal vectors representing the directions of maximum variance in the data. Subsequently, the K-means method is applied to cluster the feature vector space, with the predefined number of clusters reflecting the number of principal vectors. Each cluster represents a group of similar blocks of image differences, which helps to identify significant features associated with fractures. Finally, the DBSCAN method is employed to identify areas where points with similar characteristics are located. Subsequently, a binary fracture mask is generated, with pixels exceeding the threshold being identified as fractures. Findings. The introduced methodology attains an accuracy rate of 98.13 %, surpassing the performance of conventional methods such as DBSCAN, PCA, and K-means. Furthermore, the method exhibits a recall of 82.38 %, signifying its ability to effectively detect a substantial proportion of positive examples. Precision of 58.54 % underscores the methodology’s capability to minimize false positives. The F1 Score of 70.90 % demonstrates a well-balanced performance between precision and recall. Originality. DBSCAN, PCA and K-means methods have been further developed in the context of automated detection of building destruction in aerospace images. This allows us to significantly increase the accuracy and efficiency of monitoring territories, including those affected by the consequences of military aggression. Practical value. The results obtained can be used to improve automated monitoring systems for urban development and can also serve as the basis for the development of effective strategies for the restoration and reconstruction of damaged infrastructure.
Automatic Compensation of the Mill RolL Eccentricity in Terms of Limited Speed of Hydraulic Compression Devices
(Dnipro University of Technology, Dnipro, 2025) Boyko, O.; Kuvaiev, Victor; Potap, Oleg; Potap, M.; Rybalchenko, Maria O.
ENG: Purpose. To reduce deviation of vertical dimension (thickness) of rolled products from the specified value by enhancing the accuracy and shortening the setup time of an eccentricity compensation subsystem of mill rolls based on substantiation of an eccentricity compensation method. This method is based on an active search algorithm to determine the actual eccentricity parameters in real time, taking into account the actual response time of hydraulic compression devices (HCD) and investigating its effectiveness through simulation computer modelling. Methodology. The research was based on the analytical determination of the frequency characteristics of the AGC system in sheet metal rolling, considering the actual response time of HCD of a rolling mill as well as a comprehensive model of a rolling process in a quarto mill with rolling movement and an automatic thickness control system (ATCS) that compensates for eccentricity. The study was conducted by comparing the results of computer simulation modelling of the improved ATCS, whose algorithm took into account the HCD response time, with the performance indicators of the previous system, which did not consider this factor. Findings. It has been established that under the AGC thickness control conditions, the measured amplitude of a variable component of thickness does not match the amplitude of eccentricity due to the finite response time of HCD. The frequency characteristics of the AGC system have been determined analytically, taking into account the actual response time of HPD in a rolling mill. An improved procedure for determining the actual eccentricity amplitude in real time has been substantiated, which involves a temporary reduction in the HCD speed within the initial rolling section. A structure for an automated control system has been proposed for practical implementation of this procedure. It has been demonstrated that the proposed solutions allow for a threefold reduction in thickness variations caused by eccentricity compared to the corresponding performance indicators of the known eccentricity compensation systems with the AGC thickness control. Originality. The influence of the HCD response time on the accuracy of AGC thickness control systems for rolled products has been established. An approximate linear relationship has been identified between the ratio of the amplitude of thickness fluctuations caused by eccentricity and the amplitude of roll gap fluctuations relative to the roll speed and HCD response time under the AGC algorithm thickness control conditions. The improved procedure for determining the actual eccentricity amplitude in real time has been substantiated. Practical value. The effectiveness is substantiated of implementing an improved active search algorithm for determining the eccentricity parameters of mill rolls under the limited HCD response conditions in real time. This approach allows for a threefold reduction in the sheet thickness variability caused by roll eccentricity compared to the performance indicators of the known AGC thickness control systems, thereby ensuring the production of high-precision rolled products in Ukrainian sheet rolling mills.
CFD Modeling of Traffic-related Air Pollution in Street Canyon
(Printing House “Technologija”, Kaunas, Lithuania, 2024) Biliaiev, Mykola M.; Biliaieva, Viktoriia V.; Berlov, Oleksandr V.; Kozachyna, Vitalii A.; Kozachyna, Valeriia V.; Yakubovska, Zinaida M.
ENG: High pollution levels are often observed in urban street canyons. Different mathematical models are intensively used to predict pollution levels in urban street canyons. In this paper quick computing 3D CFD model is proposed to compute wind flow over buildings and pollutant dispersion in street canyon. To simulate wind flow over buildings 3D equation of potential flow has been used. Pollutant concentration field has been modelled using three-dimensional equation of pollutant dispersion. Governing equations are also included simplified equations to describe pollutants chemical transformations in atmosphere. To solve numerically governing equations implicit difference schemes have been used. The computer code to realize the proposed numerical models has been developed. Results of numerical experiments are presented.
Change in Slag Composition and Sulfur Content of Hot Metal in the Process Chain of Blast Furnace — Hot Metal Desul furization Complex — Converter (BOF)
(Publishing House “Akademperiodyka”, Kyiv, 2024) Shevchenko, A. P.; Kysliakov, Volodymyr G.; Dvoskin, B. V.; Manachyn, Ivan O.
ENG: Introduction. Modern conditions of iron and steel making industry require production of high-quality competitive metal products. Thus, the removal of sulfur at the lowest cost has been becoming increasingly important. Problem Statement. The major amount of sulfur in iron and steel making comes with charge materials in sintering blast furnace production. When using out-of-furnace processing of hot metal in hot metal desulfurization and slag removal facilities, the degree of hot metal desulfurization can be 75—99%. This ensures the production of hot metal with a sulfur content in the range of 0.002—0.015%. Purpose. The analysis of changes in the sulfur content of hot metal and in the slag composition in the process chain of steel production, followed by the development of technical solutions and process methods to eliminate the resulfurization of hot metal. Materials and Methods. Our calculations, based on the actual data of Ukrainian and Chinese iron and steel making facilities. The selected samples of slag and hot metal have been analyzed with the use of raster spectral microscopy methods. In the studies of sulfur content at various stages of smelting, the method of material balance calculation has been employed. Results. In the slag phase, along with systems of CaO ∙ SiO2 ∙ Al2O3 type with different ratios of components containing 0.2—3.5% sulfur, CaxSiyAlz type systems containing up to 1% sulfur have been detected. In the beads, the sulfur content varies within 0.1—0.85%. Sulfur is present in the form of sulfides of (Fe, Mn)S type, mainly MnS, while in non-metallic inclusions of the beads, the sulfur content ranges within 15—30%. The residing ladle slag after desulfurization should not exceed 0.5—0.7 kg/t of hot metal. Conclusions. To prevent the resulfurization of hot metal during its discharge from a blast furnace, it is advisable to rationalize ladle slag modes, by adjusting ladle slag composition, increasing the degree of ladle cleaning from the slag residing from previous loads and inducing a slag cover in the absence of ladle slag. The conducted studies have shown that sulfur from the slag does not return to the hot metal and resulfurization does not occur, which is explained by the protective effect of residual magnesium.
Coefficient of Local Loss of Mechanical Energy of the Flow for a Mixture of Charge Materials
(Dnipro University of Technology, 2021) Selegej, Andriy Mikolayovich; Ivaschenko, Valeriy; Golovko, Vjacheslav Iljich; Kiriya, R.; Kvasova, Luydmila Sergijvna
ENG: Purpose. To determine the dependence of the coefficient of local losses of mechanical energy of flow of a twocomponent mixture of charge material on its depth, content of components, and average equivalent diameter of particles in the case of their freedispersed motion. Methodology. The value of the coefficient of local losses of mechanical energy was determined by the value of the hydraulic resistance of the fluid during its movement in open channels and pipes. In this paper, methods were used of comparative analysis, mathematical modeling and forecasting of dynamic processes in the flow of granular material. findings. Based on the results of theoretical studies, a mathematical model was obtained, the use of which allows calculating the coefficient of local losses of mechanical energy for the flow of a twocomponent mixture of charge materials with agglomerate particle sizes from 15 to 50 mm, pellets from 6 to 12 mm, coke from 10 to 60 mm. The developed model with satisfactory accuracy makes it possible to evaluate the movement of the charge from the indicated materials along the paths of the charging devices of blast furnaces at a speed in the range from 1.5 to 20 m/s and to determine the trajectories of the mixture of charge materials on the top with an accuracy of 0.2 m. It is noted that the calculation of the above coefficient by the known techniques is not accurate enough, which is associated with the uncertainty in the choice of a single average equivalent diameter of the particles of the two component charge. Comparative analysis of the developed model with the known models and experimental data indicates that the accuracy of calculating the dynamic parameters of a twocomponent flow of charge materials using the developed model increases by 5–10 % in comparison with calculations using the previously known models. Originality. For the first time, regularities of changes in the coefficient of internal mechanical losses of a twocomponent flow of charge materials from its depth, content of components, average equivalent particle diameters when moving along the paths of charging devices of blast furnaces have been established. practical value. Mathematical dependencies have been developed and can be used to determine the technological parameters of the charge of a modern blast furnace with different characteristics of the granulometry of the charge and the ratios of its components. This will increase the accuracy of predicting the course of the process under consideration, the degree of automation of the control systems for the technological process of the charge supply of blast furnaces, will make it possible to use expensive charge materials more efficiently, reduce energy consumption and reduce the harmful impact on the environment.
Comparative Analysis of Classification Methods for High-Resolution Optical Satellite Images
(Khmelnytskyi National University, Khmelnytskyi, 2024) Hnatushenko, Volodymyr V.; Kashtan, Vita; Chumychov, Denys; Nikulin, Serhii
ENG: High-resolution satellite image classification is used in various applications, such as urban planning, environmental monitoring, disaster management, and agricultural assessment. Traditional classification methods are ineffective due to the complex characteristics of high-resolution multichannel images: the presence of shadows, complex textures, and overlapping objects. This necessitates selecting an efficient classification method for further thematic data analysis. In this study, a comprehensive assessment of the accuracy of the most well-known classification methods (parallelepiped, minimum distance, Mahalanobis distance, maximum similarity, spectral angle map, spectral information difference, binary coding, neural network, decision tree, random forest, support vector machine, K-nearest neighbour, and spectral correlation map) is performed. This study comprehensively evaluates various classification algorithms applied to high-resolution satellite imagery, focusing on their accuracy and suitability for different use cases. To ensure the robustness of the evaluation, high-quality WorldView-3 satellite imagery, known for its exceptional spatial and spectral resolution, was utilized as the dataset. To assess the performance of these methods, error matrices were generated for each algorithm, providing detailed insights into their classification accuracy. The average values along the main diagonal of these matrices, representing the proportion of correctly classified pixels, served as a key metric for evaluating overall effectiveness. Results indicate that advanced machine learning approaches, such as neural networks and support vector machines, consistently outperform traditional techniques, achieving superior accuracy across various classes. Despite their high average accuracy, a deeper analysis revealed that only some algorithms are universally optimal. For instance, some methods, such as random forests or spectral angle mappers, exhibited strength in classifying specific features like vegetation or urban structures but performed less effectively for others. This underscores the importance of tailoring algorithm selection to the specific objectives of individual classification tasks and the unique characteristics of the target datasets. This study can be used to select the most effective method of classifying the earth's surface, depending on the tasks of further thematic analysis of high-resolution satellite imagery. Furthermore, it highlights the potential of integrating machine learning-based approaches to enhance the accuracy and reliability of classification outcomes, ultimately contributing to more practical applications.
Comparative Mathematical Analysis of Transmission and Axial Disc Brakes
(Український державний університет науки і технологій, Дніпро, 2024) Monia, Andrii G.; Bychkova, D. M.
ENG: Purpose. A comparative study of axial and transmission disc-pad brakes. The task of the work is the theoretical determination of the braking torque and the force of pressing the pads against the disk in different braking modes, as well as the determination of the area of optimal operating modes of the indicated brakes. The methods. Comparative mathematical analysis. Findings. With equal dimensions of the two types of disc brakes and an even distribution of the braking torque between the wheel pairs, the transmission creates a greater braking torque on each of the four wheels of the traction section due to the gear ratio of the axial gearbox. Installing a disc brake on the axle of a wheel pair with a central location of the drive gear wheel allows you to change the masses of the half-axles, which means to eliminate self-oscillations that destroy the drive axle under the action of resonant torsional vibrations. The heavier the rolling stock of the train being transported, or the greater the slope of the track on the descent, the smaller the braking torque can be applied to the wheel pair, to exclude its blocking and clutch failure. The obtained results show that the smaller the moments of inertia and stiffness of the wheels, half-axles and transmission elements (gear wheels, shafts, etc.), the smaller the braking torque required to stop the locomotive on the same braking path. But the higher the speed of the train before braking, the greater the braking torque should be. Originality. The obtained results show that the smaller the moments of inertia and stiffness of the wheels, half-axles and transmission elements (gear wheels, shafts, etc.), the smaller the braking torque required to stop the locomotive on the same braking path. But the higher the speed of the train before braking, the greater the braking torque should be. Practical value. Taking into account the above-mentioned features of disc brakes, multilevel backup of brake systems of heavy mining locomotives operating on track slopes of up to 50 ‰ should be considered justified and necessary. Such locomotives should have both disc transmission brakes, as more efficient, and disc axle brakes as safer.
Complex of Mathematical Models and Methods to Calculate Pressure Effect on Sulfide Distribution in Steel
(Хмельницький національний університет, Україна, 2021) Selivyorstova, Tetjana V.; Selivyorstov, Vadim Yu.; Kuznecov, Vitaliy V.
ENG: Primary objective is to develop computational method to analyze digital pictures of sulfide prints, helping obtain qualitative image characteristics, and to formulate mathematical model of the distribution of sulphide inclusions to determine specific features of the pressure effect on the macrostructure formation of carbon steel castings flooded into the uncooled mold. The research was carried out using images of sulfide prints of templates cut of steel cylindrical castings; L500 steel was applied. The castings result from industrial tests of a method of gas-dynamic effect on the fusion in the foundry forms under the conditions of a casthouse of Dnipropetrovsk aggregate plant PJSC. Digital pictures of sulfide prints, obtained in terms of the increased rate of gas pressure and maximum pressure, were binarized; defective fra gments were removed; and zo ning took place. The developed computational method has been applied for fragments of images, representing different zones; data arrays have been received containing sizes and amounts of inclusions in the fragment. The developed computational method to analyze digital images of sulfide prints has been implemented. ASImprints software support has helped obtain qualitative characteristics of images; namely, distribution of amount of the certain-size sulfide inclusions. The computational method to analyze digital images of sulfide prints has made it possible to study the set of patterns of sulfide prints. The dependences have been obtained, describing specific features of sulfide inclusion distribution while varying gas-dynamic pressure method in terms of fusion in the casting form. It has been demonstrated that the distribution describes effectively the power-series distribution to compare with the exponential one. Mathematical model of the power -series distribution parameter dependence upon pressure has been developed. Deviation of the distribution parameters in terms of the experimental values and the model values has been evaluated. The research demonstrates the ways to apply an algorithm of simple recursive casting for quantitative analysis of digital images of sulfide prints. Use of ASImprints, being software implementation of the computational method to analyze digital images of sulfide prints making it possible to obtain qualitative characteristics of images, has helped identify that the increased pressure within a casting-device for gas injection system results in the increased specific amount of inclusions and the decreased specific zone of sulfide inclusions respectively. It has been defined that exponential function describes reliably the nature of sulfide inclusion distribution in the digital image of sulfide print. The research has demonstrated that fragments of a sulfide print, belonging to one zone, are statistically homogeneous. Thus, it is possible to analyze quantitively digital image zone of a sulfide print on its fragment. Mathematical model of dependence of sulfide inclusion distribution in carbon-steel castings in terms of gas-dynamic effect on fusion solidifying in a mold has been developed. The model may be applied to predict sulfide inclusion distribution within the selected zones of cross section of the cylindrical castings solidifying in the uncooled mold in terms of the preset mode of gas-dynamic effect.
Computer Modeling of Harmful Impurities Transfer
(Scientific Publishing Center “Sci-conf.com.ua”, 2021) Moroz, Borys Ivanovych; Shvachych, Gennady Grygorovych; Chorna, Valentyna Ivanivna; Voroshylova, Nataliiya Volodymyrivna
ENG: The paper considers solutions to the ecology problems, which set is formulated from cause-effect relationships. According to the adopted model, the equation’s coefficients for the harmful impurities transfer are attributed to the causal features of the process. Herein, the setting of cause-and-effect links is the goal of the ecology’s direct problems. Along with direct methods of mathematical modeling of harmful impurities transfer in the atmosphere from pollution sources, the paper considers the formulation and methods of solving inverse problems, which essence is to estimate the input parameters based on actual information about the modeled system, known from the experiment. Based on the research results, a software package was developed to implement the solution of the coefficient inverse problems of ecology using the mathematical modeling method.
Computer Modeling of Territory Flooding in the Event of an Emergency at Seredniodniprovska Hydroelectric Power Plant
(Dnipro University of Technology, Ukraine, 2022) Ivanov, D. V.; Hnatushenko, Volodymyr V.; Kashtan, Vita Yu.; Garkusha, I. M.
ENG: Purpose. Computer modeling of territory flooding in the event of an emergency at Seredniodniprovska Hydroelectric Power Plant (HPP). Methodology. The computer model of possible territory flooding at Seredniodniprovska HPP is developed using simulation modeling methods and geometric and hydrological approaches and considers initial boundary conditions of the water-engineering system. Calculations of the wave break height and the half-divided cross-sectional area of the river bed were made and a three-dimensional model of the territory flooding was built using the Python language and ArcGIS Desktop software. Findings. The data for each creation of the hydraulic node, namely the depth and width of the flooded territory, were calculated. This allowed analyzing the macro level considering the triangulation model of the surface. The wave break parameters and flaps (intersections) were taken into account in case of a dam break at a hydroelectric power plant or a rise in the water level. A mathematical model, and a 3D model were developed, and a forecast of the flood zone due to an emergency was made using satellite survey data. Originality. The mathematical method received further development for calculating flood territories in the event of an emergency at Seredniodniprovska Hydroelectric Power Plant, taking into account the parameters of the breakthrough wave and the calculation of cross-sections for the cases when a hydroelectric dam breaks or the water level rises; the method uses one-dimensional and two-dimensional systems of Saint-Venant equations, and geometric and hydrological approaches. A three-dimensional model of the territory flooding is developed to predict possible consequences. Practical value. The obtained results can be used to model the flooding of the territory located near dangerous hydro-technical objects, such as dams, dikes as well as to forecast flooded territories during the construction of drainage and protective structures.
Computer System for Mechanisms Diagnosis
(Ukrainian State University of Science and Technologies, Dnipro, 2022) Ivashchenko, Valeriy; Shvachych, Gennady; Sushko, Larysa
ENG: The computer system proposed in this work is aimed at solving the problem of automating a comprehensive assessment of the technical functioning of mechanisms. The system’s computational equipment have the minimum necessary computing requirements. No additional paid software is required for installation. Unlike existing systems, the proposed one has a moderate cost. For the majority of industrial enterprises, this factor is crucial when choosing the most beneficial computer system. In addition, the developed system is simple and comfortable to use. Thus, the system has an intuitive and intelligible interface for the operator, which allows the operator to quickly familiarize themselves with it and put it to use immediately; the system monitors the correctness entries in the electronic history - it corrects basic fields that are not properly indicated (repair data, repair requests, part price, etc.). The system has the ability to add individual templates for a specific unit. Unlike existing systems, the proposed system is multifunctional.