Chinese Journal of Aeronautics最新文献

Insects usually fly by passively rotating wings, which has been applied to the design of flapping-wing Micro-Air Vehicles (MAVs) to reduce mechanical complexity. In this paper, a robotic passive rotating-wing model is designed to investigate wing kinematics and lift generation, which are measured by a high-speed camera and a force transducer, respectively. In addition, flow fields are measured using the Particle Image Velocimetry (PIV). Experimental results demonstrate that passive rotating motion has a coordinative relationship with actively stroking motion. As the stroke amplitude or frequency increases, the rotating amplitude is enlarged. To characterize the active stroking motion, a driving Reynolds number Re_driving is defined, which varies from 68 to 366 in this study. Moving the gravity center of the wing towards trailing edge induces the increase of additional torque M, which decreases the wing rotating amplitude and promotes the advance of wing rotation. We find that the timing of wing rotation is gradually delayed and the mean lift coefficient $\overline{C_L}$ monotonously decreases as Re_driving increases. By increasing the additional torque M, $\overline{C_L}$ is slightly improved and approaches to the lift coefficient of a real fruit fly at driving Re approximately equal to 230. The instantaneous lifts combined with the vortical structures further demonstrate that the lift generation associated with wing rotation is mainly attributed to the growth of the Leading-Edge Vortex (LEV) and the passive wake capture mechanism. Passive wake capture is influenced by LEV, reversal stroke motion and wing additional torque together, which can only maintain the lift at a high level for a considerable period. The high-lift generation mechanisms of flapping and passive rotating flight could shed light on the simplified design of MAVs and the improvement of their aerodynamic performance.

Carbon Nanotubes (CNTs) reinforced Polymer-Matrix Composites (PMCs) is widely used as insulation materials in thermal protection system of aerospace propulsion. However, CNTs are prone to oxidation and have high thermal conductivities, which makes it difficult to improve the ablation resistance of insulation materials that contain CNTs. SiO₂ was encapsulated onto the surface of CNTs (CNTs@SiO₂), which were then added to Ethylene Propylene Diene Monomer (EPDM) rubber to prepare the insulation materials. Thermogravimetric analysis and ablation test were used to evaluate the resistance of the insulation materials to thermal oxidation and ablation. Additionally, scanning electron microscopy was performed to analyze their microstructures. Results revealed that the addition of CNTs@SiO₂ could visibly reduce the effects of hot corrosion and ablation on insulation materials. The C-CNTs@SiO₂-1 formulation had the best ablative resistance. Further, compared with the unencapsulated formulation (C-CNTs-10), the C-CNTs@SiO₂-1 formulation reduced the line ablation rate by 51% to 0.0130 mm/s after oxygen-acetylene experiments. Lastly, the ablation mechanism was investigated based on the effects of the CNTs@SiO₂ additive on their properties. Thus, the improvement in ablation performance may be attributed to CNTs@SiO₂-induced decreases in thermal conductivity, improvement in the hot corrosion resistance in the char layer, and changes in the microstructure.

Lunar dust is considered to be one of the top challenges for enabling humans to have extended stays on the moon. Human activities such as module landings and launches, walking, rover operation and construction activities will inevitably produce a significant amount of dust. Therefore, it is important to estimate the potential range and intensity of dust deposition caused by these activities to minimize dust accumulation over time and for maintenance planning and execution. A modular model that correlates the dust deposition distribution with initial mean dust particle velocity, its mean ejected angle and the total amount of ejected mass is developed for an elementary mechanical movement. This modular model is further employed to form a modeling framework to estimate dust deposition of a trajectory based activity of similar repeated movements such as the landing process of a lander, walking and rover operation. The model forms a unified modeling framework for different trajectory-based activities and is shown to predict consistent and physically meaningful ranges and intensities of dust deposition provided reliable data to calibrate the model parameters.

In the process of stage separation of recoverable liquid launch vehicles, because of the large amount of residual fuel in the storage tanks, the influence of liquid sloshing on separation safety must be considered. Considering calculation simplicity and operation practicability, the Moving Pulsating Ball Model (MPBM) of large amplitude liquid sloshing is introduced into the calculation of launch vehicle stage separation. Combining the dynamic equation of the model with the energy relationship during “breathing movement”, the formula calculating the force of liquid on the rigid body is derived. Compared with the calculations of commercial CFD calculation software, the accuracy of MPBM model is verified. Then, all the external forces and moments are applied to the rigid body of the stages, so that the translational and rotational dynamic equations of the stages are obtained respectively. According to the relative position of the two stages, the geometric shape of the interstage section and the engine of the second stage, the minimum clearance in the separation process can be decided to guarantee that the separation process is safe.

Wind is the primary challenge for low-speed fixed-wing unmanned aerial vehicles to follow a predefined flight path. To cope with various wind conditions, this paper proposes a wind disturbance compensated path following control strategy where the wind disturbance estimate is incorporated with the nominal guiding vector field to provide the desired airspeed direction for the inner-loop. Since the control input vector for the outer-loop kinematic subsystem needs to satisfy a magnitude constraint, a scaling mechanism is introduced to tune the proportions of the compensation and nominal components. Moreover, an optimization problem is formulated to pursue a maximum wind compensation in strong winds, which can be solved analytically to yield two scaling factors. A cascaded inner-loop tracking controller is also designed to fulfill the outer-loop wind disturbance compensated guiding vector field. High-fidelity simulation results under sensor noises and realistic winds demonstrate that the proposed path following algorithm is less sensitive to sensor noises, achieves promising accuracy in normal winds, and mitigates the deviation from a desired path in wild winds.

Thermally-induced flow instabilities are a critical issue in multi-channel regenerative cooling systems. In particular, the interactions between Density-Wave Oscillations (DWO) and Flow Maldistribution (FMD) can result in complex and disastrous instability phenomena. This study investigates the instability behaviors of hydrocarbon fluid in a four-channel system with a constant heat flux ratio using both frequency- and time-domain methods. As the heat flux increases, the in-tube flow sequentially destabilizes in each channel and converges to new equilibrium states, leading to the emergence of FMD phenomena. This also causes the system eigenvalue to change repeatedly from negative to positive rather than increasing monotonically. Additionally, the system eigenvalues are between those of the two most unstable channels, indicating that the stability behavior of the entire system is dictated by the most unstable channel. After FMD occurs, flow oscillations are activated in channels with weak stability, and the in-tube flow is observed to evolve into various flow patterns, including stable flow, self-sustained oscillation, oscillation divergence, quasi-periodic oscillation, and oscillation excursion. The novel instability mode of oscillation excursion involves a spontaneous transition of operating states. It oscillates from an equilibrium state and then stabilizes at a new operational state after oscillation-induced redistribution. However, the newfound stable state may also be only temporary, with the in-tube flow regressing to the initial state, resulting in quasi-periodic oscillation.

A multi-body dynamic rigid-flexible coupling model of landing gear is established to study the gear walk instability caused by the friction characteristics of the brake disc. After validating the model with the experimental results, the influence of the landing gear structure and braking system parameters on gear walk is further investigated. Among the above factors, the slope of the graph for the friction coefficient of the brake disc and the relative velocity of brake stators and rotors is the most influential factor on gear walk instability. Phase trajectory analysis verifies that gear walk occurs when the coupling of multiple factors causes the system to exhibit an equivalent negative damping trend. To consider a more realistic braking case, a back propagation neural network method is employed to describe the nonlinear behavior of the friction coefficient of the brake disc. With the realistic nonlinear model of the friction coefficient, the maximum error in predicting the braking torque is less than 10% and the effect of the brake disc temperature on gear walk is performed. The results reveal that a more negative friction slope may contribute to a more severe unstable gear walk, and reducing the braking pressure is an effective approach to avoid gear walk, which provides help for future braking system design.

Inspired by flight biology, morphing flight technology has great potential to improve the adaptability and maneuverability of aircraft. This paper is devoted to the flight control problem of morphing aircraft, and aimed at safe and fuel-saving flight through morphing actively. Specifically, the longitudinal dynamics of a morphing aircraft with telescopic wings is modelled as a strict-feedback nonlinear system. Through fitting the expression of aerodynamic parameters by the morphing ratio, the model uncertainties induced by morphing errors are embedded in the dynamics. To meet the safety and fuel-saving requirements, an Adaptive Coordinated Tracking Control Scheme (ACTCS) is then proposed, which consists of a morphing control module and a tracking control module. For the morphing control module, an on-line morphing decision model is given in an optimization process with respect to the morphing ratio, and a second-order tracking filter is introduced to smooth the decision output and ensure the physical realizability. For the tracking control module, the novel adaptive controllers for the velocity and altitude subsystems are proposed based on the dynamic surface control method, in which adaptive mechanisms are designed to compensate for the model uncertainties. Finally, the proposed ACTCS is simulated in nine different cases of the test flight mission, to verify its effectiveness, robustness and fuel-saving effect.

The seamless trailing edge morphing flap is investigated using a high-fidelity steady-state aerodynamic shape optimization to determine its optimum configuration for different flight conditions, including climb, cruise, and gliding descent. A comparative study is also conducted between a wing equipped with morphing flap and a wing with conventional hinged flap. The optimization is performed by specifying a certain objective function and the flight performance goal for each flight condition. Increasing the climb rate, extending the flight range and endurance in cruise, and decreasing the descend rate, are the flight performance goals covered in this study. Various optimum configurations were found for the morphing wing by determining the optimum morphing flap deflection for each flight condition, based on its objective function, each of which performed better than that of the baseline wing. It was shown that by using optimum configuration for the morphing wing in climb condition, the required power could be reduced by up to 3.8% and climb rate increases by 6.13%. The comparative study also revealed that the morphing wing enhances aerodynamic efficiency by up to 17.8% and extends the laminar flow. Finally, the optimum configuration for the gliding descent brought about a 43% reduction in the descent rate.

Deep learning significantly improves the accuracy of remote sensing image scene classification, benefiting from the large-scale datasets. However, annotating the remote sensing images is time-consuming and even tough for experts. Deep neural networks trained using a few labeled samples usually generalize less to new unseen images. In this paper, we propose a semi-supervised approach for remote sensing image scene classification based on the prototype-based consistency, by exploring massive unlabeled images. To this end, we, first, propose a feature enhancement module to extract discriminative features. This is achieved by focusing the model on the foreground areas. Then, the prototype-based classifier is introduced to the framework, which is used to acquire consistent feature representations. We conduct a series of experiments on NWPU-RESISC45 and Aerial Image Dataset (AID). Our method improves the State-Of-The-Art (SOTA) method on NWPU-RESISC45 from 92.03% to 93.08% and on AID from 94.25% to 95.24% in terms of accuracy.