RUDN Journal of Engineering Research
Editor-in-Chief: Yury N. Razoumny - Professor, Doctor of Technical Sciences, Director of the Academy of Engineering of RUDN, Director of the Department of mechanics and mechatronics
ISSN: 2312-8143 (Print) ISSN: 2312-8151 (Online)
Founded in 2000. Publication frequency: quarterly
Open Access: .
APC: no article processing charge
Peer-Review: double blind. Publication language: Russian, English
PUBLISHER: Peoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University)
Journal History
Indexation: Russian Index of Science Citation, Google Scholar, Ulrich's Periodicals Directory, WorldCat, Cyberleninka, East View, Dimensions, DOAJ, ResearchBib, Lens, Research4Life, JournalTOCs, British Library, Bodleian Libraries (University of Oxford), Ghent University Library
The journal publishes original articles on various topics in aviation and space technology, mechanical engineering. It makes a significant contribution to the development of Russian engineering schools and promotes promising research projects supporting their practical implementation.
The journal discusses topical issues of aviation, rocket and space technology, engineering, etc.
Current Issue
Vol 25, No 2 (2024)
- Year: 2024
- Articles: 8
- URL: https://journals.rudn.ru/engineering-researches/issue/view/1780
- DOI: https://doi.org/10.22363/2312-8143-2024-25-2
Full Issue
Articles
Algorithmic Support for Spectral Processing of Cardiograms
Abstract
The method of recording electrocardiograms as a non-invasive research method is widely used in modern functional diagnostics. Spectral diagnostic methods based on Fourier transform and wavelet transform are being developed. For the purposes of identification of cardiac rhythm disorders, the method of research selected is spectral (frequency) analysis of short-term ECG recordings, up to one period of heartbeats. Fourier series decomposition of the cardiac signal (ECG) in EDF-format for one period was carried out. It is determined that the maximum accuracy of cardiac signal description is achieved at the number of harmonics equal to half of the number of sampling points of the cardiac signal during the period. The correctness of the script developed for spectral analysis was checked by reconstructing the cardiac signal from its spectrum and comparing it with the original signal. The correlation between the spectrum and the shape of the cardiac signal has been established. The conclusion is made about the applicability of the spectral analysis method for the identification of heart rhythm disorders, as well as about the possibility of using the spectrum of electrical signals of heart contractions as a multidimensional function of the heart state. The direction of further identification of regularities by means of statistical analysis with interpretation of results by specialized specialists is indicated. The theoretical and practical value of this study lies both in determining the areas of application of spectral analysis of the cardiac signal for diagnosis and treatment, and in the practical results obtained, which can be used in the development of an expert system or a specific technical device.
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Technical Solution to Decrease Cavitation Effects in the Kaplan Turbine Blade
Abstract
Application of Kaplan turbines is widespread in low-water-head and large-capacity hydropower plants. An understanding of the failure mechanism of Kaplan Turbines is a key factor to provide useful solutions for their prevention or early treatment and to guarantee their workability. The long-term performance of Kaplan turbines depends on many factors such as cavitation, erosion, fatigue, and material defects. Cavitation in Kaplan turbines leads to flow instability, vibrations, surface damage, and reduce the machine performance. Therefore, this paper investigates the factors leading to cavitation in Kaplan turbine and presents practical solutions for it. Thermal-sprayed coatings are frequently applied due to their high wear resistance, cost effectiveness, weight reduction, and less negative impacts on base metal. Moreover, HVOF is used to create coatings with a high density and bonding strength. At high temperatures, cermet coatings, including nanoparticles, exhibit exceptional wear resistance. WC-based nanostructured and multifaceted coatings are utilized due to their high wear resistance. In addition, chromium carbide in WC-based coatings increases their oxidation and wear resistance.
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Load Distribution Between Rolling Elements of Roller Bearings
Abstract
A method for determining the degree of loading of rolling elements in the working area of roller radial single-row bearings has been developed, according to this method the load distribution between rolling elements in the working area of these bearings depends on their location in this zone and the size of the contact pad between the maximally loaded rolling element and the outer ring of the bearing. Using the developed methodology, the radial force acting on the bearing is calculated for specific examples. As a result, the ratio between the radial force of the bearing and the force acting on the most loaded rolling body is obtained, which differs from the calculation of these bearings accepted in modern practice. It is also shown that this ratio is not constant, but depends on the magnitude of the force acting on the most loaded rolling body and the size of the rings and rolling bodies of the bearing. In this regard the following is proposed, in order to determine the maximum load on the rolling bodies-rollers in the working area of the bearing using the developed methodology, the method of iterations or successive approximations is suggested to be used, the essence of which consists in the initial approximate determination of the force acting on the most loaded rolling body, subsequent determination of the load on the bearing and comparing it with the actual force. By repeating this process many times, it is possible to obtain the maximum force acting on the rolling elements in the working area of the bearing with any degree of accuracy.
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Investigation of the Effect of Thermal Cycling on the Magnetic and Mechanical Properties of Steels
Abstract
Currently, throughout the world, thermal cycling processes are recognized as the most effective ways to increase the durability of metalworking tools. However, this promising technology has been little studied for structural steels. But the question of the influence of thermal cycling on magnetic properties (coercive force) has practically not been raised in the scientific literature. Therefore, in this work, the goal was to study the change in the coercive force and hardness of steels when using various thermal cycling schemes. During the experiments, steels of various purposes (structural and instrumental) and chemical composition were investigated. The following were studied: - pendulum, lowtemperature, medium-temperature, high-temperature thermal cycling and thermal cycling near the Curie temperature of cementite. All standard types of thermal cycling showed a drop in coercive force. Thermal cycling for carbon structural steel was carried out near the Curie point of cementite. The steel showed a jump in properties during the third cycle. A study of the structure revealed that partial spheroidization of pearlite occurred despite the fact that thermal cycling took place below the line of phase transformations. Research has shown that granular pearlite has a significantly greater coercive force than lamellar pearlite. The issue needs further research, and the phenomenon must find its practical application.
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Building a Predictive Model for Predicting Real Estate Prices Based on the Generated Database
Abstract
The work is devoted to solving the current problem of forecasting real estate prices by building a predictive model based on the generated database of real estate in Moscow, posted on the Move Real Estate website. Existing machine learning methods for solving the forecasting problem are considered and one of them is applied - multiple linear regression. A regression analysis of the obtained results of solving the forecasting problem was carried out. Eleven independent variables are considered as control parameters. The influence of the variables taken into account when constructing the model on the results of solving the problem of forecasting real estate prices was studied. It was determined which of the independent variables have the greatest impact on the results of the model. To improve the quality of the model, preprocessing and standardization of features were carried out. Identification of outliers and omissions of values was carried out during the formation of the database. The coefficients of the multiple linear regression model were determined using the least squares method. To assess the quality of the model, the following model parameters are analyzed: R-squared, adjusted R-squared, p-value. The result of constructing a predictive model is the resulting regression equation. The application of the resulting equation can be used to subsequently take into account specific characteristics when solving the problem of forecasting real estate prices. The work shows the advantages of using this method and the prospects for applying the obtained result.
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The Role of Convolutional Neural Networks in Cricket Performance Analysis
Abstract
Significant insights have arisen from an extensive review of the current literature, highlighting the importance of Convolutional Neural Networks (CNNs) in cricket performance analysis and mapping new directions for future research. Despite difficulties such as limited availability of data, processing difficulty, and interpretability issues, incorporating CNNs into cricket statistics is a potential effort made possible by advances in machine learning and deep learning methods. Instructors, players, and data analysts can use CNNs to better comprehend the game, extract meaningful information from video data, and improve decision-making processes. Key findings show that CNNs are effective tools for a variety of cricket analysis tasks involving batting, bowling, fielding, and player tracking. The use of CNNs represents an advancement in cricket analysis, promising to open up new aspects of performance and usher in a data-driven era of cricket genius. Augmenting data, the use of parallelization, explainable AI, and concerns about ethics, provide opportunities to address current challenges can be identified as future advances in sports analysis with CNNs. Embracing technological advancements and mapping out future research directions are critical steps towards realizing this revolutionary potential.
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The Dual Aspects of Legal Reasoning in the Era of Artificial Intelligence - Defeasible Reasoning and Argumentation Scheme
Abstract
The age of artificial intelligence emphasises the possibility of justification and the dialectical aspects of legal reasoning. The need for validity in legal reasoning mainly stems from the existence of exceptions to rules and conflicts between rules. Formal logic may well account for exceptions to rules and thus characterise cancellable reasoning. The presented article focuses on legal issues related to Artificial Intelligence (AI) that are being discussed in the scientific community because of their importance for understanding the mechanisms of law realisation. Some of the most pressing issues in the application of artificial intelligence include: transparency of algorithms, cybersecurity vulnerabilities, unfairness, bias and discrimination, lack of adversariality, legal personality issues, intellectual property issues, adverse effects on employees, privacy and data protection issues, liability for damages and lack of liability. Recognising the importance of artificial intelligence in the field of law, and acknowledging that the field requires constant reassessment and flexibility, this article develops a discussion that is important given the seriousness of the impact of artificial intelligence technologies on legal actors. on legal issues related to Artificial Intelligence (AI) that are being discussed in the scientific community because of their importance for understanding the mechanisms of law realisation. Some of the most pressing issues in the application of artificial intelligence include: transparency of algorithms, cybersecurity vulnerabilities, unfairness, bias and discrimination, lack of adversariality, legal personality issues, intellectual property issues, adverse effects on employees, privacy and data protection issues, liability for damages and lack of liability. Recognising the importance of artificial intelligence in the field of law, and acknowledging that the field requires constant reassessment and flexibility, this article develops a discussion that is important given the seriousness of the impact of artificial intelligence technologies on legal actors.
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Improving the Capacity of the Carriageway of the City Streets of Karbala
Abstract
The religious and economic importance of the city of Karbala led to an increase in the number of daily trips and an increase in the flow of traffic, therefore it was necessary to know the city’s road network. This study deals with the evaluation of the traffic performance of urban streets of the study area. The survey was conducted for several days, in the morning and the evening. The data obtained for the selected roads at a distance of 200 m are engineering data, traffic data, and side friction data. The results showed that the values of side friction occurred during the morning and evening rush hours, which affect the decrease in the average speed by 51% because of the side friction was very high.
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