Current Issue : April-June Volume : 2025 Issue Number : 2 Articles : 5 Articles
Recently, the so-called fi ft h generation (5th) aircraft have been introduced into the air forces, including the already implemented American F-22 and F-35, the Russian Su-57 and the Chinese-made J-20. Little is known about the latter, but the fi rst squadron of Su-57 is being formed, which will ultimately replace the fourth generation (4th) Su-35 aircraft . Nowadays, in global political turmoil, the mentioned aircraft can pose a real threat to NATO defense systems. Therefore, the performance of Russian 4th and 5th generation combat aircraft has been evaluated. This is quite interesting because the aircraft comes from the same Sukhoi design bureau, and the experience of the predecessor was utilized to develop the new one. Thus, it was possible to assess the impact of modern technologies and design methods on the performance of the new generation combat aircraft . To evaluate the performance of the aircraft , the method based on the so-called Energy Maneuverability theory was used, based on the method cited, the Swiss company ALR Aerospace has developed a commercial program that is used in the process of modern aircraft design. The program was utilized in this study to determine the performance and assess the capabilities of the 4th and 5th generation combat aircraft . The essential aircraft ’s data for the cited program were taken from relevant military portals, the aircraft manufacturer’s website, monographs on the design of combat aircraft , papers, and even confi dential sources. However, some of the aerodynamic parameters were obtained by comparing the aircraft used by the Polish Air Forces (F-16 and MiG-29) with a similar mission profi le or parameters and performance. The outcomes of work can be helpful, for example, at the stage of air threat assessment and simulations and anti-aircraft defense systems....
This study presents a comparative analysis of the corrosion and mechanical properties of an Al-SiC composite and an AA 2024 aluminum alloy, focusing on their suitability for aeronautical applications. The Al-SiC composite was fabricated using advanced powder metallurgy techniques, incorporating a 20% volume of silicon carbide (SiC) particles, averaging 1.6 μm in size, to enhance its structural and electrochemical performance. Electrochemical evaluations in an aerated 3.5% NaCl solution revealed a significant improvement in the corrosion resistance of the Al-SiC composite. This enhancement is attributed to the cathodic nature of the SiC particles, which promote the formation of a protective aluminum oxide layer, reducing piing corrosion and preserving the material’s structural integrity. In terms of the mechanical properties, the Al-SiC composite demonstrated a higher yield strength and ultimate tensile strength compared to the AA 2024 alloy. While it exhibited a slightly lower elongation at failure, the composite maintained a favorable balance between strength and ductility. Additionally, the composite showed a higher Young’s modulus indicating improved resistance to deformation under load. These findings underscore the potential of the Al-SiC composite for demanding aerospace applications, offering valuable insights into the development of materials capable of withstanding extreme operational environments....
When icing, aerodynamic surfaces of the aircraft, negative changes in the impact of the air flow on them occur, which leads to a noticeable drop in wing lift, a decrease in the efficiency of the rudders, a decrease in the aircraft and loss of control. In order to optimize the complex of technological equipment for anti-icing treatment of the aircraft, the necessary studies of materials and methods of anti-icing treatment of aircraft were carried out, based on the KNO-AERO-MA complex, designed for processing (washing, anti-icing protection) of the outer surfaces of aircraft, due to the existing pumping equipment in the system of collecting and returning the spent solution. The essence of the filtering technology is to clean solutions from harmful impurities through a special porous medium, the so-called filter. The created simplified model of a high-speed pressure vertical filter made it possible to study one or more filter links of the filter column. According to the research results, in order to optimize the technological equipment complex during aircraft anti-icing treatment, in the system of collecting and returning spent solutions for repeated anti-icing treatment of aircraft, it is recommended to use a highspeed pressure vertical granular filter. The introduction of such a system will allow servicing several aircraft simultaneously, significantly reduce the cost price and improve the environmental friendliness of this technological process. Keywords: icing, aircraft aerodynamic surfaces, optimization of the technological equipment complex, aircraft anti-icing treatment, system of collecting and returning spent solution, filtration technologies, high-speed pressure vertical granular filter, reduce the cost price, improve the environmental friendliness of the process....
Artificial intelligence (AI) can be used to optimize the prediction of pressure fluctuations over the external surfaces of aerospace launchers and minimize the number of wind tunnel tests. In the present research, various machine learning (ML) techniques capable of predicting the acoustic load were tested and validated. The methods included decision trees, Gaussian Process Regression (GPR), Support Vector Machines (SVMs), artificial neural networks (ANNs), linear regression, and ensemble methods such as bagged and boosted trees. These algorithms were trained using experimental data from an extensive wind tunnel test campaign conducted to support the design of a VEGA (Advanced Generation European Vehicle) launcher vehicle and provide wall pressure fluctuations in many configurations. The main objective of this study was to identify, among several algorithms, the most suitable method able to process such complex databases efficiently and to provide reliable predictions. Different statistical indices, including the root mean square error (RMSE), the mean square error (MSE), and a correlation coefficient (R-squared), were employed to evaluate the performance of the ML methods. Among all the methods, the bagged tree algorithm outperformed the others, providing the most accurate predictions, with low RMSE and high R-squared values across all test cases. Other methods, such as the ANNs and GPR, exhibited higher errors, indicating their reduced suitability for this dataset. The results demonstrate that ensemble decision tree methods are highly effective in predicting acoustic loads, offering reliable predictions, even for configurations outside the training database. These findings support the application of ML-based models to optimize experimental campaigns and enhance the design of aerospace launch vehicles....
There is growing international interest in assessing population exposure to radiofrequency electromagnetic fields, especially those generated by mobile-phone base stations. The work presented here is an experimental study in which we assess exposure to radiofrequency electromagnetic fields in a university environment, where there is a site with mobile-phone antennas and where a large number of people live on a daily basis. The data were collected with a personal exposure meter in two samplings, one walking at ground level and the other using an aerial vehicle at a height higher than the buildings. The geo-referenced electric-field data were subjected to a process in which a theoretical model was adjusted to the experimental variograms, and heat maps were obtained using kriging interpolation. The research carried out is of great relevance, since it provides detailed measurements of the electromagnetic radiation levels both at ground level and at significant heights, using innovative methodologies such as the use of drones. Furthermore, the results obtained allow for contextualizing the exposures in relation to international safety limits, highlighting the importance of rigorous monitoring in everyday environments....
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