Aerospace Defense

Abstract The security and survivability of defensive structures against extreme dynamic loads such as blast waves and impacts is a fundamental priority in modern design. Sandwich panels, due to their exceptional strength-to-weight ratio and high energy absorption capacity, are among the primary candidate materials in this field. This research investigates and compares the influence of two widely used core types the porous core and the viscoelastic core on the natural frequencies of a sandwich beam structure. The main objective of this study is to assess the potential of these cores to enhance the strength and safety of defensive structures through the analysis of their vibrational behavior. The present research employs analytical modeling to perform the natural frequency analysis. Using three-layer sandwich beam theory and applying Hamilton's principle, the governing equations of the system are derived. The resulting equations are complex partial differential equations (PDEs). To solve these equilibrium equations, the semi-analytical Navier method is utilized in the spatial domain. To validate the accuracy of the obtained results, comparisons are made with existing solutions for specific cases. Finally, the influence of various parameters such as carbon nanotube volume fraction, porosity coefficient, porosity distribution pattern, geometric and dimensional ratios on the natural frequencies of the sandwich structure is examined. This investigation covers structures with both porous and viscoelastic cores and nanocomposite face sheets. A key finding of this research is that, in most instances, the viscoelastic core exhibits higher natural frequencies and greater strength compared to the porous core.

Abstract The performance of naturally aspirated aircraft engines declines significantly with increasing altitude due to reduced air pressure and density, affecting power, torque, in-cylinder pressure, and combustion temperature. This study presents a comparative analysis of the carbureted (Rotax 912 ULS) and fuel-injected (Rotax 912iS) versions of the Rotax 912 engine using GT-SUITE simulations across altitudes up to 9,150 meters. Results indicate that the carbureted engine suffers an 80% reduction in power at high altitudes due to its fixed fuel-air mixture, while the fuel-injected engine maintains more stable performance by dynamically adjusting fuel delivery. The EFI system also preserves higher in-cylinder pressure and combustion stability under oxygen-scarce conditions. Although EFI mitigates performance loss more effectively than carburetion, both configurations exhibit significant degradation at high altitudes, highlighting the inherent limitations of naturally aspirated engines. These findings underscore the importance of advanced altitude compensation methods—such as turbocharging or optimized EFI mapping—for enhancing reliability and efficiency in high-altitude aviation operations.

Abstract Accurate estimation of attitude and heading in UAVs is one of the key challenges in autonomous navigation systems, playing a vital role in the control and guidance of these vehicles. In this paper, a quaternion-based particle filter with a specific sampling method and an extended Kalman filter (EKF) are employed for UAV attitude estimation. By integrating data from inertial sensors (including gyroscopes, accelerometers, and magnetometers) and applying filtering techniques, the proposed methods significantly enhance the accuracy of roll, pitch, and yaw angle estimation. The innovation of this study lies in the comprehensive comparison of the particle filter and EKF performance across two scenarios: simulated data and real-world data collected from a specific attitude and heading reference system (AHRS). The results demonstrate that the particle filter achieves remarkable improvements of over 99.99% in simulated data and over 88.48% in real-world data for roll and yaw angle estimation. Additionally, the analysis of variance and standard deviation of errors confirms that the particle filter outperforms in reducing error dispersion, with the error variance for yaw angle being approximately 100 times lower than that of the EKF. On the other hand, the EKF shows slightly better performance in pitch angle estimation. These findings suggest that a combination of these two filters can serve as an effective solution for precise navigation systems in UAVs. The resampling method implemented in the particle filter also significantly enhances the accuracy of roll and yaw angle estimation.

Abstract This study focuses on the thermal analysis of the cooling system for a specific type of enclosed motor pump. According to the IEC standard, the winding insulation has a specific temperature tolerance; exceeding this limit can damage the insulation and impair motor function. A crucial component of the motor's cooling system is the waterjacket, which serves two purposes: cooling the motor housing and cooling the flow passing through the motor interior. Reducing the motor housing temperature ultimately lowers the winding temperature. To simplify calculations, a thermal analysis of the enclosed motor housing was performed, considering temperature and thermal boundary conditions. The effect of the waterjacket at various flow rates 0.1, 0.3, and 0.5 kg/s and the coil flow at flow rates of 0.05, 0.1, and 0.15 kg/s, along with different diameters, were investigated to determine temperature and pressure drop. The heat generated in different motor components was applied as a heat flux on the inner surface of the motor housing. The results show that increasing the waterjacket flow rate consistently reduces the housing temperature and the coil outlet fluid temperature. Conversely, increasing the coil flow rate increases the coil outlet temperature. Using a water-antifreeze mixture compared to pure water slightly increases the minimum housing temperature. The minimum housing temperature consistently occurs at a coil flow rate of 0.05 kg/s and a waterjacket flow rate of 0.5 kg/s. The pressure drop always increases with increasing waterjaket flow rate

Abstract The performance of air defense and cyber defense systems is highly dependent on the interactions among multiple operational parameters. However, exhaustive evaluation of all possible parameter configurations is computationally infeasible due to the exponential growth in the number of combinations. To address this challenge, this paper proposes a covering array-based testing approach that leverages an Improved Ant Colony Optimization (ACO) algorithm to generate an efficient set of test scenarios. By incorporating enhanced path selection mechanisms and adaptive pheromone updating strategies, the proposed algorithm achieves faster convergence and higher coverage quality compared to the classical ACO. The method was validated on a simulated multi-parameter air defense system, where the results indicate a reduction of more than 90% in the required test cases while ensuring complete coverage of all critical t-way interactions. Furthermore, the proposed approach is adaptable to the testing of command-and-control systems, electronic warfare platforms, and cyber defense networks.

Abstract Pitting corrosion is one of the most destructive forms of localized metal degradation and poses a serious threat in aerospace structures, particularly in the presence of chloride ions. Conventional epoxy coatings have limited durability against aggressive agents and mechanical damage. The aim of this study was to develop and evaluate an epoxy coating modified with a hybrid nanocomposite of reduced graphene oxide and zeolitic imidazolate framework in order to enhance resistance to pitting corrosion and improve self-healing ability. The hybrid nanocomposite was synthesized through an in-situ growth method and incorporated into the epoxy matrix. The prepared coatings were applied on steel substrates and cured, then analyzed using chemical and microstructural techniques. Their corrosion performance was assessed by electrochemical tests, salt spray exposure, cathodic delamination, and adhesion evaluation. The results showed that the coating containing reduced graphene oxide and the zeolitic framework exhibited the highest electrochemical resistance and protective efficiency. In time-dependent tests, this coating demonstrated a continuous increase in resistance, while in scratched areas it formed a compact and uniform protective layer that effectively prevented corrosion propagation. The synergistic action of the graphene barrier effect and controlled release of zinc ions and imidazole molecules contributed to inhibiting anodic and cathodic reactions, thereby reducing the corrosion rate significantly. The novel epoxy coating reinforced with reduced graphene oxide and metal–organic framework provided long-term and stable protection against pitting corrosion by combining barrier and active inhibition mechanisms. This approach offers a promising pathway for the development of smart and self-healing next-generation coatings.