Aerospace Science and Technology最新文献

The use of hydrogen as a fuel is a promising way to reduce the emissions of civil aviation but it requires the development of wholly new injectors for the combustion chamber. Thanks to the increase in available computing power, the application of optimization techniques combined with CFD computations is now possible to develop these injectors. Among the optimization approaches, Bayesian optimization is particularly relevant when the objective functions and constraints of the optimization problem are expensive to evaluate which is the case in CFD-based optimization. Besides, the use of a multifidelity strategy allows to reduce the simulation cost of the Bayesian method. Therefore, this paper investigates the application of a multifidelity and multi-objective Bayesian approach to improve the performances of a laboratory swirl injector using hydrogen and operating in conditions close to industrial targets. This optimization study combines LES simulations as high-fidelity model with 2D RANS simulations as low-fidelity.

This paper proposes a fault-tolerant control scheme for tracking and controlling hypersonic vehicles with unknown dynamics, actuator failures, and unmeasurable states. The approach involves using a radial-based neural network to approximate the unknown dynamics and reconstruct the entire system model. Additionally, a neural network state observer is proposed to estimate the unmeasurable state of the system. To address the impact of actuator faults, a nonlinear observer is designed to estimate and compensate for the approximation error of the neural network system and fault values. Furthermore, a prescribed performance function is introduced to ensure both transient and steady-state performance of the system. The bounded stability of the closed-loop system is demonstrated through Lyapunov stability analysis.

A detailed analysis of transonic aerodynamics of a pitching conceptual Boeing Truss-Braced Wing (TBW) section has been carried out at various Mach numbers at a typical reduced frequency, k = 0.15. A new important flow feature of hysteresis loop cross-over has been discovered through the analysis of the $c_l$ hysteresis loops. Transonic dip has been located at M = 0.87, where the mean $c_l$ attains a minimum value. Hysteresis loop cross-over and transonic dip are important in the transonic flutter analysis of these wing sections. High fidelity database for the TBW section corresponding to different M in the range [0.7 - 0.9] has been generated by numerically solving the Navier-Stokes equations on a supercomputer at the NASA Advanced Supercomputing Division. A regularization-based machine learning (ML) methodology has been developed to predict the transonic aerodynamics of the pitching TBW section, using the training data as a subset of this high fidelity database. The ML model was then tested on test data as a subset of this database exclusive of the training data. Each ML model prediction is achieved well within a minute of computing time, as opposed to tens of hours of super-computing time required for each high fidelity CFD solution, thus making it a feasible tool for the design of a TBW, with the wing flutter in perspective. The TBW section flow was simulated corresponding to an altitude of 44,000 ft.

Incremental Nonlinear Dynamic Inversion (INDI) has received substantial interest in the recent years as a nonlinear flight control law design methodology that features inherent robustness against bare airframe aerodynamic variations. However, systematic studies into the robust design benefits of INDI-based control over the classical divide-and-conquer philosophy have been scarce. To bridge this gap, this paper compares the setup of hybrid INDI with a standard industry benchmark that is based on two-degree-of-freedom gain-scheduled proportional-integral-derivative control. This is done on an architectural basis and in terms of achievable robust stability and performance levels with respect to a common set of design requirements. To this end, a non-smooth, multi-objective $H_{\infty }$-synthesis algorithm is used that incorporates mixed parametric and dynamic uncertainties in the design objective and constraints. It is shown that close similarities exist between hybrid INDI design and gain-scheduled PID control, which leads to virtually equivalent robustness and performance outcomes in both linear time-invariant and linear time-varying contexts. It is therefore concluded that the main benefit of the hybrid INDI does not lie in improved robustness properties per se, but in the opportunity to perform modular robust design in an implicit model-following context. Specifically, this implies that the areas of flying qualities, robustness, and nonlinear implementation are directly visible and accessible in the control law structure.

This paper studies the prescribed-time output-constrained tracking control problems for Mars entry vehicle systems. By using the properties of the time-varying high-gain function and output-constrained conditions, time-varying barrier Lyapunov functions are constructed. Based on such Lyapunov functions, time-varying adaptive controllers are designed to solve the considered problem. It is proved that the proposed controllers can drive the errors converge to zero in a prescribed time under unknown disturbances, and the control signals are bounded. Both the symmetric and asymmetric cases are considered. Finally, the effectiveness of the proposed methods is illustrated by several numerical simulations.

Experimental measurements and numerical simulation methods for obtaining aerodynamic noise face issues such as high costs and long periods. A single machine learning method for predicting aerodynamic noise also requires a sufficient amount of data. According to this, this paper proposes a hybrid method integrating Random Forest and Compressive Sensing (RF_CS) to accurately reconstruct transonic buffet aerodynamic noise from sparse data. First, the RF algorithm, known for its strong nonlinear feature extraction capabilities, is used to obtain the basis function. Then, the basis coefficients are calculated using the L1 optimization algorithm based on limited sensor data and basis functions. Finally, a linear combination of basis functions and basis coefficients is used to reconstruct aerodynamic noise, including power spectral density, sound pressure level, and flow modes. Compared to the Compressive Sensing based on Proper Orthogonal Decomposition (POD_CS), the proposed algorithm can effectively reduce error by approximately 2–20 times and decrease the absolute error of modes by about 2–3 orders of magnitude. Specifically, the RF_CS method ensures that the reconstruction errors for power spectral density across various flow conditions are all below 3E-3, achieving generalization from one flow condition to the entire sample space. Additionally, this approach can utilize approximately 10 sensors to reconstruct accurate sound pressure level and modes, with errors within 5E-3 and 5E-5, respectively. This allows for generalization across the entire Mach number space based on a single Mach number condition.

Crashworthiness has been and will continue to be the main concern in aircraft design. Crash tests are essential approaches to investigate the crashworthiness of civil aircraft. Videogrammetric methods have been employed in crash tests to overcome the disadvantages of laborious, time-consuming measurement data collection using contact sensors. However, previous methods using a single pair of cameras still face challenges in large-scale applications due to the inherent contradiction between measurement range and accuracy. In this paper, a videogrammetric method using four high-speed cameras is proposed to measure the full-field three-dimensional (3D) dynamic deformation for evaluating the impact response characteristics of the full-scale crash test aircraft. Increasing the number of high-speed cameras not only can enhance the resolution and then measurement accuracy of object, but also expands the measurement range significantly. To ensure the performance of digital image correlation (DIC) used for large-scale measurement range, a speckle pattern optimization design and fabrication method is presented to generate the random speckle with uniform spraying size and density. A global calibration method based on the high-precision total station is proposed to unify the data of different stereovision subsystems. The implementation of the proposed method is illustrated through a 6.0 m/s full-scale crash test using a civil aircraft approximately 24 m in length. The impact velocity, full-field displacement and strain of the fuselage structure are measured. The results show that the test data are complete and reliable. After the vertical crash at 5.71 m/s, the lower structure of the cabin floor is seriously deformed, and the upper structure of the fuselage in the central wing area is obviously deformed due to the inertia effect of the wing. The stiffness difference of the different fuselage segments results in significant differences in dynamic response. The higher the stiffness is, the smaller the deformation. This work may provide some valuable technical insights that could support the crashworthy design, verification, and certification of civil aircraft.

Hypersonic air-breathing vehicles, utilizing ramjet and scramjet propulsion systems, are emerging as a promising option for future hypersonic transportation due to high specific impulse. The performance of hypersonic aircraft is significantly influenced by their flight trajectory, as combustion efficiency and aerodynamic forces vary markedly with altitude. Although numerous studies have focused on optimizing these trajectories, they have not adequately considered the potential for operational failures in the propulsion system, such as unstart and blowout. This study introduces a trajectory optimization approach for hypersonic aircraft that proactively addresses and mitigates these operational failures. This is achieved by establishing an operational classification process for a dual-mode scramjet engine and proposing a failure mode avoidance strategy using a Gaussian process classifier. Optimized ascent trajectories are achieved through the development of a two-stage robust sequential convex programming approach. The results of trajectory optimization indicate that the failure mode avoidance strategy proposed is crucial in obtaining minimal time trajectories, and that the optimal trajectories include drop motion in the initial stage flight in order to increase combustion efficiency.

A new design scheme for the functionally graded material (FGM) sandwich cylindrical shell structure made of ceramic-FGM-carbon fiber composites is proposed, which is geared towards supersonic flight vehicles and has high specific stiffness and high-temperature resistance. We focus on analyzing the nonlinear resonant responses of the novel FGM sandwich cylindrical shell subjected to external excitation and aerodynamic force. Firstly, the mechanical properties of the novel FGM sandwich material are calculated, and then the nonlinear dynamic model of the FGM sandwich cylindrical shell is established based on the first order shear deformation theory (FSDT) and Hamilton's principle. Due to the axisymmetric property of the cylindrical shell, a 1:1 internal resonance between the driven and companion modes always exists in the perfect cylindrical shell. Taking this into consideration, the nonlinear resonant response problems of the FGM sandwich cylindrical shell are numerically simulated by combining the Galerkin method and the pseudo-arc length continuation method. Finally, the effects of complex parameters such as external excitation, aerodynamic force, aspect ratio, gradient index, and skin-core-skin ratio on the nonlinear resonant responses of the FGM sandwich cylindrical shell are investigated.

This paper considers the impact of the random distribution of yarn properties on the mechanical and failure behavior of ceramic matrix composites (CMCs) structures and proposes an integrated analysis method based on preform-structure. Tensile tests of CMCs tip shroud specimens were carried out, and the digital image correlation technique was used to record the deformation of the specimens in real-time during loading. Based on the actual structure, a preform model of the CMCs tip shroud was established, and the kernel density estimation method was used to obtain the distribution of the yarn cross-sectional area. The random distribution of the cross-sectional area is equivalent to material properties, simulating the dispersion of the performance of CMCs. The progressive damage method simulates the failure mode during the specimen's loading process. The peak load error is 1.5 %, and the failure modes such as transverse shear damage, stitching yarn fracture, and interlaminar separation were successfully predicted.