Browse Topic: Aircraft
Aircraft assembly systems, as a critical phase in aerospace manufacturing, face significant challenges in maintaining production efficiency and ensuring product quality. This complex manufacturing system exhibits two distinct characteristics: (1) tightly coupled interactions among manufacturing elements involving process sequences, material flows, and equipment utilization; and (2) dynamic resource allocation and material distribution plans. The inherent variability in production element configurations often leads to operational instability and schedule deviations, which may result in abnormal production states. To address these challenges, this study proposes a data-driven predictive framework that integrates Long Short-Term Memory (LSTM) neural networks with multi-criteria evaluation. The developed LSTM-based model effectively forecasts two critical production indicators of cycle time and balance rate, achieving temporal prediction through historical operational data analysis. The proposed methodology facilitates timely anomaly detection and early warning, allowing proactive risk mitigation and ensuring sustained production system stability. This research contributes to advancing intelligent monitoring and control strategies for aircraft assembly operations within data-driven manufacturing environments.
To facilitate the development and application of bulb-flat titanium alloys in aerospace and automotive industries, this study selects TC4 as the research material and employs finite element simulation software to simulate the hot rolling process of TC4 bulb flat titanium. The temperature field, strain field, and metal flow velocity in each rolling pass are analyzed, and rolling experiments are conducted after optimizing the roll pass system. The results indicate that during the rolling process of TC4 bulb flat titanium, the head undergoes relatively smaller deformation, resulting in a slower temperature decrease, whereas the waist experiences greater deformation and a faster temperature drop. A significant temperature difference exists between the core and surface, which can be mitigated by appropriately increasing the roll temperature to reduce heat transfer. Prior to the K4 pass, the billet temperature drops to a level that may affect rolling performance, necessitating furnace reheating. Strain increases progressively with each rolling pass, with higher values observed at the waist compared to the head. A gradual strain transition occurs at the interface between the head and waist. Furthermore, the irregular design of the roll pass leads to a considerable difference in metal flow velocity between the upper and lower surfaces. During the K1 pass rolling, this imbalance can cause the guide guard to be displaced upward and result in roll wrapping. Without altering the roll diameter, shifting the entire roll pass system toward the side with higher metal flow velocity effectively reduces the linear velocity and prevents these issues, ensuring stable billet rolling. Rolling experiments successfully produced the final TC4 bulb flat titanium, thereby validating the feasibility of the optimized roll pass system and the rationality of the selected rolling parameters. It provides the possibility for its development and application in fields such as aircraft and automobiles.
The malfunction of the aircraft windshield electric heating system, particularly arc discharge, poses a serious threat to flight safety by causing glass breakage. A systematic study was conducted on the causes and effects of arc faults on windshield structural integrity, employing macroscopic observation, microscopic analysis, and energy dispersive spectroscopy (EDS) following a windshield fracture incident. The results indicate that arc discharge typically occurs at the interface between the heating film busbar and adjacent structures. Localized high temperatures cause the outer glass to fracture, generating radial cracks. The ablation of the busbar silver coating and the carbonization of the PVB interlayer are direct evidence of arc action, whereas the heating wire remains a passive component affected by the high-temperature environment. The fault is primarily attributed to local disbonding at the busbar interface and moisture ingress. Based on the findings, recommendations are proposed for process optimization and inspection method improvement, providing a basis for the safe design and maintenance of windshield structures.
Regarding the external sling load system of heavy-lift helicopters, the influence of the law of lifting point position on flight control stability characteristics has not been distinctly explained. To address this challenge, this paper constructs a sling load flight simulation model based on multi-body dynamics. Overall, the proposed model consists of four parts, including the rotor aeroelastic coupling model, the fuselage rigid body dynamics model, the flexible sling model, and the slung object rigid body model. Furthermore, through the hub six-degree-of-freedom rigid model and the flexible sling model, this paper realizes the dynamic coupling between the components. On this basis, taking the CH-53E heavy-lift helicopter as the research object, this paper utilizes real flight test data to validate the multi-body dynamic model. Subsequently, this paper systematically analyzes the influence of different lifting points’ lateral position, sling load mode, load-mass ratio, and forward flying speed on helicopter control stability characteristics. Simulation results indicate that the lifting point location exerts a significant impact on the helicopter’s trim attitude angles and dynamic stability. Of them, the lifting point location of the front center of gravity is the optimal in terms of trim characteristics and eigenvalue distribution. Furthermore, within a certain flight speed range, the lifting point of the front center of gravity demonstrates superior speed adaptability and system robustness. Apart from providing a solid theoretical basis for the lifting point layout design of the external sling load system of heavy-lift helicopters, the research results have important engineering application value for improving the safety of sling load flight of heavy-lift helicopters.
This paper presents the design, implementation, and validation of an aerial-launch FPV (First-Person View) drone system that was developed to provide a complex environment with flexible deployment and precise delivery capabilities. The integrated system is composed of a hybrid VTOL carrier aircraft, a number of FPV drones, and an aerial mounting / release equipment. Using the AYK-250 platform, the carrier has a vertical take-off and landing function and long-time endurance. In terms of the FPV drones, it is built upon the high performance MARK4 5-inch frame that has high agility and high payload. The release module uses a single-hook point structure with a limit stop. The FPV drones are released stably, and the separation is reliable in flight. Comprehensive flight tests proved all workflows completely, involving carrier take-off, cruise with drones mounted, sequential aerial launch, and subsequent autonomous attitude recovery and route tracking by the FPV drones. The test results confirm the system’s capability for reliable launch from an aerial platform coupled with precise guidance, establishing a credible technical solution for expanding the practical applications of FPV drones in distributed tasks. Results show that our system can be launched via an aerial platform with an accurate guide and is a viable technological solution to spread FPF Drones for operational strategies in a more distributed way.
Aerodynamicists around the globe are developing mechanisms and structures inspired by nature that enable variable camber morphing (VCM) for aerodynamic surfaces. The implementation of the VCM mechanism in an airplane wing enhances the performance and stability during various flight segments. The present review article is focused mainly on the up-to-date VCM methods in a qualitative as well as quantitative approach that are specific to Aircraft/unmanned aerial vehicle (UAV) wing configurations. Initial literature discussions are confined to the conventional mechanisms that enable VCM in different aircraft configurations and the added aerodynamic advantages such as lift enhancement, drag reduction, boundary layer separation, and flow control. However, those designs need either external shape optimization or internal structural refinements to ensure the factor of safety (FoS). The modern aviation industry is also focused on bioinspired technology because of the adaptive flying capabilities and stall-delay characteristics. Therefore, a review of bioinspired VCM methods that are assessed based on the aerodynamic potentials is sequentially organized in the article. Additionally, considerations are motivated by the application of various compliant structural patterns for VCM in the aircraft industry. The discussion indicates the prospective benefits of morphing toward the future of the Green Aviation industry.
In response to the current airworthiness regulations’ inability to cover the stall flight test requirements under icing conditions of civil aircraft with high-angle-of-attack restriction function and the lack of relevant flight test technologies in China, a study was conducted on the differences in airworthiness provisions for stall characteristics under icing conditions of such aircraft. Key technologies, including simulated ice accretion stall flight test methods, ice installation strategies, and data analysis techniques, are proposed and successfully applied to a specific civil aircraft. The results demonstrate that the methodologies proposed in this paper can effectively support simulated ice accretion stall tests, providing valuable insights for other similar aircraft.
Civil aircraft, as typical complex product systems, exhibit characteristics such as a high concentration of high-tech technologies, strong interdisciplinarity, a high level of system integration, long development cycles, substantial project investments, and complex management. During the R&D process of civil aircraft projects, there are often high risks in performance, cost, and schedule. Delays in the schedule can lead to losses in project manpower and material resources, as well as project failure. A mature objective criteria system for maturity assessment provides a reference basis for determining whether the project has reached its optimal state at a specific stage, thereby reducing project management risks and increasing the probability of project success. This research will adopt a research approach combining theoretical studies with practical case analysis. First, it will conduct extensive and in-depth investigations into various maturity models and their applications across the entire product lifecycle within relevant fields. A requirement maturity model and requirement maturity KPI (Key Performance Indicator) indicators will be established to clarify the maturity status of requirements at different development stages, enabling judgment of whether the project is ready to proceed to the next development phase. Concurrently, by developing a KPI statistical system platform integrating application servers and data processing tools, a scientific and quantitative inspection mechanism will be implemented to visualize project development progress, status, and risk data. This will provide actionable insights for project decision-making and achieve effective project management and control.
Terminal guidance is critical for ensuring strike precision in the final phase of flight. However, traditional methods, such as proportional navigation and optimal guidance laws, face significant challenges regarding real-time performance and adaptability to dynamic targets. To address these issues, neural networks offer a promising solution by enabling adaptive adjustments to guidance parameters, thereby improving performance under various constraints.
This paper, for the first time, applies the Divine Religions Algorithm (DRA) to three-dimensional UAV path planning. Targeting the complex terrain of urban-mountain mixed environments, we propose a novel method that incorporates multiple enhancements, including A* initialization, single-point disturbance mutation, and adaptive weighting. First, the A* algorithm is employed to generate high-quality initial paths, serving as the skeleton of the population. Innovative mechanisms such as terrain-adaptive disturbances and dynamic weight adjustment are integrated to achieve both efficiency and robustness in path optimization. Comparative experiments with Genetic Algorithm (GA) and Crowned Porcupine Optimization (CPO) show that the improved DRA algorithm exhibits significant advantages in terms of path length, safety margin, average altitude variation, average turning angle, and overall cost function. It consistently obtains superior paths and achieves faster convergence. The results demonstrate that the proposed approach provides an efficient, adaptive, and practical intelligent optimization tool for UAV path planning in urban-mountain mixed or similarly complex environments, offering promising prospects for engineering applications.
This paper proposes a UAV combat simulation method integrating AFSIM and DoDAF to address the complexity of UAV combat systems. DoDAF establishes a multi-view architecture mode to clarify logical relationships between UAVs and weapon systems, laying a structured foundation. AFSIM implements dynamic simulation of combat processes by mapping DoDAF’s static architecture to its dynamic elements, simulating UAV maneuver, situation awareness, and strikes. A UAV search-and-strike mission scenario test shows the method accurately simulates collaborative behavior in target searching, tracking, and engaging. This method features a high degree of standardization and normalization, providing a foundation for the evaluation of UAV combat effectiveness and strategy optimization.
Efficient optimization of aerodynamic shapes is a critical challenge in aircraft design. Traditional CFD-based optimization workflows suffer from high computational costs and low efficiency, which severely restricts their practical engineering application. In this paper, a novel aerodynamic optimization method based on a hierarchical neural network with adaptive activation functions is proposed. The network adopts learnable B-spline activation functions and is hierarchically constructed in accordance with the sharing status of B-spline control points. After being trained to achieve fast and accurate prediction of aerodynamic performance, the network can effectively replace the traditional CFD module in the optimization loop. The primary advantage of the proposed method is that it significantly reduces the computational cost during the optimization process while ensuring that the prediction accuracy is not compromised. This work thereby presents a novel strategy and technical framework for streamlining the design process of hypersonic vehicles.
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