Enhanced ultrasonic total focusing imaging of CFRP corner with ray theory-based homogenization technique

Ultrasonic testing is effective in defect characterization and quality assurance of Carbon Fiber Reinforced Plastic (CFRP) components in the aerospace industry. Due to the coupling between complex shape and elastic anisotropy, the Phased Array Ultrasonic Testing (PAUT) and time-based Total Focusing Method (TFM) face significant challenges in the calculation of wave propagation. A wave velocity distribution model is established for a multidirectional convex corner of CFRP based on a homogenization theory and the above coupling effects are also incorporated. A ray-tracing method is proposed based on Dijkstra’s shortest path search algorithm. The predicted time of flight ensures that this technique, the homogenized TFM, could synthesize a high-quality focused image by post-processing on the full matrix capture data. Experiments on a laminate with three ?1.5 mm Side-Drilled Holes (SDHs) in different circumferential directions confirm a successful homogenized TFM imaging that all SDHs can be effectively detected. As compared to the isotropic scenario, the maximum positioning error is reduced to 0.12, 0.08, and 0.38 mm, and the Signal-to-Noise Ratios (SNRs) are increased by 2.1, 1.1, and 11.8 dB, respectively. It is suggested that the ray-tracing assisted TFM technique can effectively improve the imaging of corners in CFRP components.     

Control-oriented modeling of a high-aspect-ratio flying wing with coupled flight dynamics

The flight-structural dynamics of a high-aspect-ratio wing challenge the flight control design. This paper develops a reduced model of coupled dynamics with stability consideration. The structural dynamics are formulated with dihedrals, and the central loads drive the deformation. The control-oriented model with essential coupled dynamics is formulated. Modal sensitivity analysis and input–output pairing are performed to identify the control structure. Besides, an example of flight control design is provided to discuss the necessity of considering structural dynamics in controller design. Analytical coupled flight dynamics provide a system-theoretic approach for stability and facilitate model-based control techniques. Simulation results reveal the characteristics of flight-structural coupled dynamics and demonstrate that the influence of flexible modes should be considered in control design, especially in lateral dynamics.     

Design,modeling, and control of morphing aircraft:A review

A morphing aircraft can adapt its configuration to suit different types of tasks, which is also an important requirement of Unmanned Aerial Vehicles(UAV). The successful development of an unmanned morphing aircraft involves three steps that determine its ability and intelligent: configuration design, dynamic modeling and flight control. This study conducts a comprehensive survey of morphing aircraft. First, the methods to design the configuration of a morphing aircraft are presented and analyzed...     

Wide-range model predictive control for aero-engine transient state

To perform transient state control of an aero-engine, a structure that combines linear controller and min–max selector is widely adopted, which is inherently conservative and therefore limits the fulfillment of the engine potential. Model predictive control is a new control method that has vast application prospects in the field of aero-engine control. Therefore, this paper proposes a wide-range model predictive controller that can control the engine over a wide range within the flight envelope....     

Nonlinear adaptive flight control system: Performance enhancement and validation

The problem of decreasing stability margins in L₁ adaptive control systems is discussed and an out-of-loop L₁ adaptive control scheme based on Lyapunov’s stability theorem is proposed. This scheme enhances the effectiveness of the adaptation, which ensures that the system has sufficient stability margins to achieve the desired performance under parametric uncertainty, additional delays, and actuator faults. The stability of the developed control system is demonstrated through a series of simulations. Compared with an existing control scheme, the constant adjustment of the stability margins by the proposed adaptive scheme allows their range to be extended by a factor of 4–5, bringing the stability margin close to that of variable gain PD control with adaptively scheduled gains. The engineered practicability of adaptive technology is verified. A series of flight tests verify the practicability of the designed adaptive technology. The results of these tests demonstrate the enhanced performance of the proposed control scheme with nonlinear parameter estimations under insufficient stability margins and validate its robustness in the event of actuator failures.     

Influence of lunar regolith compressibility on sampling performance of thick wall spiral drills

A 2 m class robotic drill was sent to the Moon and successfully collected and returned regolith samples in late 2020 by China. It was a typical thick wall spiral drill (TWSD) with a hollow auger containing a complex coring system to retain subsurface regolith samples. Before the robotic drill was launched, a series of laboratory tests were carried out to investigate and predict the possible drilling loads it may encounter in the lunar environment. This work presents how the sampling performance of the TWSD is affected by the regolith compressibility. Experiments and analysis during the drilling and sampling process in a simulated lunar regolith environment were conducted. The compressibility of a typical lunar regolith simulant (LRS) was measured through uni-directional compression tests to study the relationship between its inner regolith stress and bulk density. A theoretical model was established to elucidate the cutting discharge behavior by auger flights based on the aforementioned relationship. Experiments were conducted with the LRS, and the results show that the sampling performance is greatly affected by the flux of the drilled cuttings into the spiral flight channels. This work helped in scheduling reasonable drilling parameters to promote the sampling performance of the robotic drill in the Chinese Chang'E 5 mission.     

DFCluster: An efficient algorithm to mine maximal differential biclusters for single pilot operations task synthesis safety analysis

With the continuous advancement of the avionics system, crew members are correspondingly reduced, and Single Pilot Operations(SPO) has attracted widespread attention from scholars.To meet the flight requirements in SPO mode, it is necessary to further strengthen air-ground coordination system integration, but at the same time, there will be some safety issues caused by resource integration, function fusion, and task synthesis. Aimed at the safety problems caused by task synthesis, an efficient d...     

High dynamic output feedback robust control of cascaded extended state observer

High dynamic tracking performance is a key technical index of hydraulic flight motion simulator(HFMS). However, the strong nonlinearities, various model uncertainties and measurement noise in hydraulic actuation systems limit the high dynamic performance improvement. In this paper, the outer axis frame of a HFMS is taken as a case study and its nonlinear dynamic model with consideration of strong nonlinearities, matched and mismatched uncertainties is established.A novel cascaded extended state ...     

A geographical and operational deep graph convolutional approach for flight delay prediction

Flight delay prediction has attracted great interest in civil aviation community due to its significant role in airline planning, flight scheduling, airport operation, and passenger service. Flight delay is affected by numerous factors and irregularly propagates in air transportation networks owing to flight connectivity, which brings critical challenges to accurate flight delay prediction. In recent years, Graph Convolutional Networks (GCNs) have become popular in flight delay prediction due to the advantage in extracting complicated relationships. However, most of the existing GCN-based methods have failed to effectively capture the spatial–temporal information in flight delay prediction. In this paper, a Geographical and Operational Graph Convolutional Network (GOGCN) is proposed for multi-airport flight delay prediction. The GOGCN is a GCN-based spatial–temporal model that improves node feature representation ability with geographical and operational spatial–temporal interactions in a graph. Specifically, an operational aggregator is designed to extract global operational information based on the graph structure, while a geographical aggregator is developed to capture the similar nature among spatially close airports. Extensive experiments on a real-world dataset demonstrate that the proposed approach outperforms the state-of-the-art methods with a satisfying accuracy improvement.