Aerospace Defense

Abstract Introduction: Bio-inspired cellular structures and auxetic geometries have attracted considerable attention due to their superior energy absorption capabilities and deformation characteristics. However, the combined effects of sunflower-inspired radial arrangement, re-entrant geometry, and foam filling on the mechanical response and energy absorption performance of cellular structures remain largely unexplored.
Methods: This study experimentally investigates the quasi-static compressive behavior of conventional honeycomb, sunflower-inspired, and hybrid sunflower re-entrant lattice structures in both hollow and polyurethane foam-filled configurations. The specimens were fabricated using three-dimensional (3D) printing technology with polylactic acid (PLA) material and tested under quasi-static compression.
Findings: The results demonstrated that cellular geometry significantly influences the buckling mechanism, deformation stability, and energy absorption capacity. The hybrid sunflower re-entrant structure exhibited a more uniform stress distribution and a more progressive collapse mode than the conventional honeycomb structure due to its auxetic behavior and radial–spiral arrangement. Furthermore, polyurethane foam increased the initial stiffness, delayed the onset of buckling, and improved the progressive crushing behavior. The proposed structure achieved a 112% increase in energy absorption, a 6% improvement in specific energy absorption, and a 3% enhancement in crushing force efficiency compared with the conventional honeycomb structure.
Conclusion:
The synergistic combination of sunflower-inspired geometry, re-entrant auxetic configuration, and polyurethane foam filling considerably enhances the energy absorption performance and deformation stability of cellular structures, indicating significant potential for applications in aerospace, automotive, and sandwich panel systems.

Abstract Introduction: Urban air mobility and air taxi systems have emerged as promising solutions for future transportation demands due to their potential for reducing travel time and improving transportation efficiency. However, achieving an optimal balance among aircraft weight, aerodynamic performance, fuel efficiency, and mission requirements remains a significant challenge during the conceptual design phase. Therefore, the development of intelligent optimization approaches integrated with conventional design methodologies is of considerable importance.
Methods: This study presents the optimal design of an 18-passenger air taxi through the integration of classical aircraft design methods and a Q-learning-based reinforcement learning framework. Initially, baseline parameters, including maximum takeoff weight, empty weight, fuel consumption, and wing area, were estimated using established conceptual design relations. A simulation environment was then developed in which the state space was defined by key nondimensional parameters, including thrust-to-weight ratio, wing area ratio, fuel weight ratio, and empty-weight-to-maximum-weight ratio. The action space consisted of bounded modifications to wing area, aspect ratio, and thrust-to-weight ratio. The reinforcement learning agent was trained for 2000 episodes with a maximum of 40 design steps per episode using an ε-greedy policy under a fixed mission profile defined by cruise altitude, cruise speed, range requirements, and field length constraints.
Findings: The optimization process resulted in a 3.8% reduction in wing area and a 2.1% increase in aspect ratio. Furthermore, the horizontal and vertical tail areas decreased by 2.9% and 3.2%, respectively. These geometric refinements led to reductions in empty weight (4.1%) and fuel consumption (5%). Significant improvements in aerodynamic and performance characteristics were also observed, including increases in lift-to-drag ratio (20%), rate of climb (33.3%), and cruise speed (6.7%). Consequently, the flight range increased by 14.5%.
Conclusion: The findings demonstrate that integrating classical aircraft design methodologies with reinforcement learning provides an effective and data-driven framework for improving air taxi design. The proposed approach successfully achieved simultaneous reductions in aircraft weight and fuel consumption while enhancing aerodynamic efficiency and mission performance, indicating its potential for future intelligent conceptual aircraft design applications.

Abstract Introduction: Multilayered composite structures are widely used in aerospace and engineering applications due to their high strength-to-weight ratio. However, their structural performance is highly sensitive to manufacturing defects, particularly matrix cracks, which can significantly reduce the critical load-bearing capacity and accelerate buckling failure under shear loading. Therefore, developing accurate analytical models capable of accounting for damage-induced stiffness degradation is essential for reliable structural design.
Methods: An advanced analytical model was developed to predict the critical shear buckling load of thick laminated composite plates containing matrix cracks. The formulation is based on a higher-order shear deformation theory (HSDT) with 11 degrees of freedom, which accurately captures the parabolic distribution of transverse shear stresses and transverse normal strain effects without requiring shear correction factors. Stiffness degradation parameters resulting from matrix cracking were directly incorporated into the model using experimental tensile test data. The governing equations were derived through the principle of minimum potential energy and solved using the Galerkin method.
Findings: The effects of matrix crack density (0–1 crack/mm), plate thickness-to-length ratio (a/h = 5–100), and fiber orientation angle (θ = 0°–90°) on the normalized critical shear buckling load and its reduction percentage were investigated. The results demonstrated that matrix cracking substantially decreases the buckling resistance of composite plates. For the [±45]s laminate configuration, a crack density of 1 crack/mm resulted in a reduction of up to 64% in the critical shear buckling load. Furthermore, the proposed analytical predictions showed excellent agreement with three-dimensional elasticity solutions and finite element simulations.
Conclusion: The developed HSDT-based analytical model provides an accurate and efficient tool for evaluating the shear buckling behavior of damaged thick composite plates. The results highlight the significant influence of matrix crack density on structural stability and demonstrate the necessity of considering experimentally determined stiffness degradation in buckling analyses of composite structures.

Abstract Introduction: In the present work, the X-ray diffraction (XRD) pattern of ZnSe quantum dots is simulated using a home-made computer program. ZnSe is an important semiconductor with an FCC-zinc blend stable crystalline phase owing a lattice constant of 5.6676 Å, which has widespread applications in optoelectronics, infrared detectors, and aerospace technology applications.
Methods: In this study, XRD patterns are simulated for both bulk and nanoscale ZnSe.
Findings: The results indicate that in the bulk phase, the diffraction peaks are very sharp and narrow, consistent with the standard reference cards. However, at the nanoscale, the peaks broaden and their intensity changes, indicating a reduction in crystallite size and an increase in structural defects. A comparison is made between the simulation and the experimental results, showing that the agreement between the experimental XRD pattern and the simulated one in terms of the number of peaks, their positions, relative intensities, and peak widths indicates good consistency.
Conclusion: This research confirms that XRD simulation is a powerful and efficient tool for the structural analysis of nanomaterials, capable of accurately reproducing the effects of size and defects on diffraction patterns. Therefore, the developed program can play a significant role in the analysis and design of ZnSe semiconductor nanostructures and other compounds.

Abstract ntroduction:Pitting corrosion is one of the most destructive forms of localized metal degradation and poses a significant threat to aerospace structures exposed to chloride-containing environments. Conventional epoxy coatings provide limited protection because of their inherent permeability and the absence of active corrosion-inhibition mechanisms. This study aimed to develop a hybrid nanocomposite-reinforced epoxy coating based on reduced graphene oxide (rGO) and zeolitic imidazolate framework-8 (ZIF-8) to enhance pitting corrosion resistance and improve self-healing performance
Methods:Epoxy nanocomposite coatings containing 0.5 wt.% of rGO, ZIF-8, and hybrid rGO–ZIF-8 were fabricated and applied onto steel substrates. Structural and microstructural characterization was performed using Fourier-transform infrared spectroscopy (FT-IR) and field-emission scanning electron microscopy (FE-SEM). Corrosion protection was evaluated under both intact and scratched conditions using electrochemical impedance spectroscopy (EIS), a 45-day salt spray test, cathodic disbondment, and pull-off adhesion testing
Findings:The rGO–ZIF-8/EPC coating exhibited the highest electrochemical resistance, the lowest electrolyte permeability, and the greatest protective stability among all coatings. Under scratched conditions, EIS measurements showed a sustained increase in total impedance, indicating effective active corrosion protection. Salt spray testing demonstrated that corrosion after 45 days remained largely confined to the scratched region. FE-SEM observations confirmed the formation of a more homogeneous microstructure, while pull-off testing revealed significantly improved coating adhesion.
Conclusion:The superior performance of the rGO–ZIF-8 reinforced epoxy coating is attributed to the synergistic combination of the physical barrier effect of rGO nanosheets and the controlled release of Zn²⁺ ions and imidazolate ligands from ZIF-8. This hybrid nanocomposite provides a stable, active, and self-healing protective system, making it a promising candidate for mitigating pitting corrosion in aerospace structures and other chloride-rich environments.

Abstract Introduction:Reliable and secure wireless communication is essential for unmanned surface vehicles (USVs) and autonomous underwater vehicles (AUVs), where compact antenna systems with high isolation and stable performance are required despite severe space constraints. This study proposes a compact encapsulated monopole diversity antenna designed to improve communication reliability while minimizing mutual coupling between antenna elements. Methods:A dual-band encapsulated monopole antenna with a shared circular radiator was designed and fabricated on an FR4 epoxy substrate (dielectric constant of 4.4 and loss tangent of 0.02). The antenna incorporates two perpendicular feed structures, radiator slots, a dumbbell-shaped radiator, and a ground stub to enhance impedance matching and isolation. The overall antenna dimensions are 11.4 × 5.3 × 1.6 mm, operating at 2.4 GHz and 5.8 GHz. Its performance was evaluated through simulated and experimental analyses, including S-parameters, return loss, radiation patterns, diversity gain, and envelope correlation. Findings:The proposed antenna achieved excellent impedance matching with a return loss of approximately 25 dB at both operating frequencies. The shared-radiator configuration significantly reduced the antenna size while maintaining high performance. Both simulated and measured results demonstrated approximately 20 dB improvement in isolation compared with conventional directly coupled antenna elements. In addition, the antenna exhibited satisfactory radiation characteristics, low envelope correlation, and effective diversity performance, making it suitable for reliable wireless communication in compact platforms. Conclusion:The proposed encapsulated dual-band monopole antenna provides a compact, lightweight, and high-isolation solution for unmanned surface and underwater platforms. Its shared-radiator architecture, enhanced impedance matching, and reduced mutual coupling improve communication reliability and system integration, making it a promising candidate for secure wireless applications in autonomous marine vehicles and other space-constrained systems.