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Methodology for investigating the interference immunity of satellite navigation antenna arrays using ansys hfss

2026-07-10T08:41:19Z

Назва: Methodology for investigating the interference immunity of satellite navigation antenna arrays using ansys hfss Автори: Slyusar, Vadym; Атаманюк, Ігор Петрович; Atamanyuk, Igor; Sliusar, Ihor; Shelemin, Zakhar; Sidenko, Ievgen; Kondratenko, Yuriy Короткий огляд (реферат): This paper presents an HFSS-based procedure for quantifying the interference resilience of satellite-navigation antennas on autonomous platforms that employ digital antenna arrays and controlled reception pattern antennas (CRPAs). An individual element is first simulated to determine the operating band under the VSWR<2 criterion and to select the analysis frequency. The complete array is then solved with in-phase excitation to obtain the zenith peak gain P. Next, a phase distribution that enforces a zenith null is identified, the associated gain depression D is measured, and interference suppression is expressed as P−D. The workflow is demonstrated on navigation CRPAs of several topologies. A six-element ring yields a relative null depth of about 36.5 dB, whereas a seven-element ring provides up to 45 dB of suppression. The strongest performance is achieved by a dual-ring 16-element array, reaching a 53 dB null depth. A square 4×4 array is lower by 8.5 dB. In further research, it would be advisable to experimentally test the influence of phase errors and also to extend this approach to other electromagnetic simulators.

Application of robotics for automating livestock feeding and farm management

2026-06-30T09:33:55Z

Назва: Application of robotics for automating livestock feeding and farm management Автори: Мартиненко, Володимир Олександрович; Martynenko, Volodymyr; Соколік, Віталій Дмитрович; Sokolik, Vitaliy; Плацканов, Владислав Володимирович; Plackanov, Vladislav Короткий огляд (реферат): The aim of the study was to evaluate the effectiveness of applying robotics for automating livestock feeding and farm management in Ukraine. The methodology was based on a comprehensive approach combining time recording, energy auditing, and economic analysis methods at four agricultural enterprises in the Kyiv, Cherkasy, Vinnytsia, and Poltava regions. Computer modelling (MATLAB Simulink), biosensor monitoring of animals, and advanced statistical methods (GPower, Shapiro-Wilk criterion) were used. The study found that the introduction of robotic feeding systems increased the accuracy of feed component dosing by 20.7%, feed mixing uniformity by 24.8%, reduced energy costs by 53.9%, and increased animal productivity by 12.3-13.7%. The economic feasibility is confirmed by an average payback period of 4.3 years with an internal rate of return of 27.5%, a return on investment of 34.7%, and a profitability index of 1.85. It has been determined that the most cost-effective solution is to introduce robotic systems on farms with a livestock population of 100 to 150 heads, where the use of suspended rail systems provides the best ratio of investment costs to economic benefit. The results of the study are of direct practical importance for the modernisation of livestock farms in Ukraine and can be used as a basis for the development of state programmes to support technological modernisation in the agricultural sector.

Study of Deep Subsurface Fatigue Degradation in Rolling and Sliding Tribocontacts under Variable Loading

2026-06-29T06:35:37Z

Назва: Study of Deep Subsurface Fatigue Degradation in Rolling and Sliding Tribocontacts under Variable Loading Автори: Марченко, Дмитро Дмитрович; Marchenko, Dmytro Короткий огляд (реферат): The paper evaluates the effectiveness of soft gas nitriding of alloyed structural steels 38KhMYuA, 38KhN3MA, and 38KhN3MFA, used in highly loaded gear transmissions, and establishes the limits of application of thin nitrided layers in terms of contact fatigue. The studies are conducted after nitriding at a temperature of 580°C and a duration of 7 hours using microhardness testing, layer-by-layer chemical analysis by high-temperature gas analysis, X-ray structural analysis, and contact fatigue testing of rollers simulating rolling and sliding conditions, typical for helical gearing. It is found that soft nitriding ensures the formation of a hardened layer 0.18–0.25 mm thick with a microhardness of 4.8–5.5 GPa while maintaining a ductile core with a hardness of 240–260 HB. It is shown that under elevated contact stresses, failure of nitrided samples initiates in the subsurface layers and develops via a deep contact fatigue mechanism, accompanied by the formation of deep spalling and a so-called white etching area. The results obtained demonstrate the limited effectiveness of thin nitrided layers under high contact loads and point to the feasibility of using materials with thicker hardened layers (0.8–1.2 mm) or design and technological solutions aimed at reducing contact stress and increasing the service life of gears. Опис: Повний текст доступний з сайту видавця за посиланням: https://link.springer.com/article/10.3103/S1068366626700121

Burst-Aware Cascade Detection of UAV Radio-Frequency Signals Using Energy and Cyclostationary Analysis

2026-06-22T08:11:24Z

Назва: Burst-Aware Cascade Detection of UAV Radio-Frequency Signals Using Energy and Cyclostationary Analysis Автори: Sova, Ivan; Kozlov, Oleksiy; Kondratenko, Yuriy; Кондратенко, Юрій Пантелійович; Атаманюк, Ігор Петрович; Atamanyuk, Igor; Aleksieieva, Anna Короткий огляд (реферат): The increasing activity of unmanned aerial vehicles (UAVs) has intensified the demand for reliable and computationally efficient methods for passive radio-frequency (RF) signal detection. In practical RF monitoring scenarios, the environment is often non-stationary and affected by varying noise conditions. Under such circumstances, classical energybased detectors are sensitive to noise uncertainty, while more robust approaches, such as cyclostationary analysis, require substantially higher computational resources. This work presents a burst-aware cascade method for UAV RF signal presence detection that explicitly addresses this trade-off. The proposed framework combines fast energy-based screening with temporal burst aggregation, applying spectral correlation function (SCF) analysis selectively and only when sustained signal activity is indicated. Detection is performed on fixed-length RF signal chunks, while additional segment-level duration constraints are used to characterize sustained transmissions. The method is evaluated using the publicly available DroneRF dataset and compared against six baseline detectors, including fixed-threshold energy, wavelet-based, blind cyclostationary, two adaptive energy detector variants, and a lightweight convolutional neural network. Experimental results confirm that chunk-level detection remains difficult for all considered methods. Temporal aggregation across longer intervals yields a substantial improvement: the cascade achieves Pd = 1.000 and AUC = 1.000 at the segment level, matching exhaustive cyclostationary detection while reducing per-segment processing time by a factor of 2.46. An additional result is that burst-level concatenation prior to SCF estimation provides implicit coherent integration, preserving Pd = 1.000 at signal amplitude reductions of up to −20 dB where standalone detectors degrade to Pd = 0.995. Overall, burst-aware cascade architectures offer a practical and interpretable approach to RF-based UAV monitoring, providing a well-grounded compromise between detection reliability and computational efficiency under realistic operating conditions.