Aerospace Systems最新文献

Stability is essential for the safety of Unmanned Aerial Vehicles (UAVs) and holds paramount importance in their design. This study focuses on the longitudinal stability of twin-boom UAVs with inverted V-tail and inverted U-tail configurations. Computational fluid dynamics (CFD) method and longitudinal perturbed equations of motion were employed to comprehensively analyze the stability and flight performance of these UAVs. Results indicate that the inverted U-tail configuration exhibits 23.6% higher longitudinal static stability than the inverted V-tail under small perturbations. In Phugoid mode, the inverted U-tail UAV also demonstrates superior performance. These findings provide valuable insights for the design and optimization of UAV tail configurations.

This paper proposes an intermittent measurement-based attitude tracking control strategy for spacecraft operating in the presence of sensor-actuator faults. A sampled-data (self-)learning observer is developed to estimate both the spacecraft’s states and lumped disturbances, effectively mitigating the impact of faults. This observer acts as a virtual predictor, reconstructing states and actuator fault deviations using only intermittent measurement data, addressing the limitations imposed by sensor failures. The control scheme incorporates compensation based on the predictor’s estimates, ensuring robust attitude tracking despite the presence of faults. We provide the first proof of bounded stability for this learning observer utilizing intermittent information, expanding its applicability. Numerical simulations demonstrate the effectiveness of this innovative strategy, highlighting its potential for enhancing spacecraft autonomy and reliability in challenging operational scenarios.

The aerodynamic benefits of non-smooth surfaces, such as drag reduction, are well-established, but accurately simulating their effects poses significant challenges due to increased modeling complexity and computational demands. This paper introduces an enhanced simulation method tailored for analyzing the near-wall flow fields of non-smooth surfaces. By developing a modified wall function, the proposed method replicates the flow characteristics of non-smooth surfaces on smooth walls, thereby simplifying the simulation process. The results demonstrate a marked improvement in computational efficiency, with a reduction in simulation time by more than 20%, without compromising accuracy. This approach offers a robust and efficient tool for aerodynamic optimization in engineering applications.

Use of operational data such as those from QAR (Quick Access Recorder) has recently attracted interest in building high-accuracy flight fuel models. This is often combined with applying some machine learning algorithms to improve the model’s fidelity. However, the data-based approach lacks the physical characteristics of the aircraft flight performance models and is challenging to interpret and use in optimizing aircraft designs. This paper proposes a collaborative optimization process based on a physics-based aircraft multidisciplinary sizing tool and a data model built from flight data. First, an enhanced aircraft sizing tool is used to provide initial estimation of the aircraft design parameters based on the top-level requirements. Unknown parameters in the sizing model are determined using data-based approach which include both aircraft operational and flight parameters. Aircraft operational parameters include actual passenger weight, cargo weight, fuel weight, cruising Mach number, and other essential operational parameters. Aircraft flight parameters include information on aircraft, route, and weather etc., derived from QAR data and open-source flight databases. Aircraft design, operation, and flight parameters are coupled with an aircraft performance model, which can be used in a collaborative multi-parameter optimization framework to optimize aircraft design and operations for improved fuel performance.

This review presents a groundbreaking approach for investigating low-satellite orbits through the derivation of comprehensive equations governing their motions. The present work also presents some of the forces affecting this motion at low satellite orbit levels. This paper also presents different numerical methods for solving the equations governing two-body problems. The goal is to develop a strong mathematical model for the satellite to find a suitable path for orbital movement. Due to the effects on the orbit, the orbit must be controlled. For this purpose, orbital control uses orbital maneuvers to move the satellite to the desired location. Some modern technology (intelligent modeling) was used to create a simulator to increase the mathematical accuracy of the model and control its orbit. The objective is to develop a comprehensive mathematical model of orbital motion. This includes the design of a control unit for satellite orbits and the application of optimization algorithms. Furthermore, it involves developing a neural network-based model for the orbital control system. This study aims to achieve the desired outcomes in satellite orbital motion control by integrating these components.

Multi-annular jets are derived from coaxial jets, which are used to improve the mixing of fuel and air before ignition in a gas turbine combustor and it is essential to achieving stable and effective combustion. In the present work, a multi-annular jet comprising two co-annular and one central jet has been used to understand the flow characteristics and mixing of jets in non-expanded and expanded confinement with different angular outlets. A computational investigation has been performed with different swirl combinations in three air jets inlet under non-combustion conditions. After validation from existing experimental results, parametric studies have been investigated with different expansion ratios, different swirl combinations, and different angular outlets. Using the realizable k–ε turbulence model and commercial software ANSYS FLUENT, results were obtained in the form of streamlines plots, axial velocity contours, and center line axial velocity. Following a comprehensive analysis of the computational output, it is found the mixing process in confinement depends on expansion ratios, swirl combinations, and angular outlets. Results show that the mixing of jets is enhanced in expanded confinement at particular swirl combinations and at certain angular outlets.

The objective of this paper is to enhance the combustion efficiency of a scram jet engine by varying the design parameters. The two dimensional numerical analysis is carried out with four different strut model using the k epsilon method for this study with the Mach number of 2 to evaluate the combustions efficiency and pressure loss. The results shows that strut model design 4 is providing the maximum efficiency of 99% with the total pressure loss of 3.08043 × 10⁵ Pa compare to other strut model. The novelty of the model is to vary the two parameter like strut configuration along with fuel injection locations to enhance the combustion efficiency with minimum increment of pressure loss at supersonic conditions. This proposed method can be used for scramjet and supersonic related applications.

The processing and application of time series are widespread, including tasks like weather forecasting, traffic flow prediction and intention recognition. However, in reality, missing data often occurs due to target occlusion or sensor failures. Many deep learning models are designed for uniformly sampled complete data and cannot be directly applied to scenarios with missing values. Traditional data preprocessing methods, such as imputation and interpolation, introduce additional noise. To address these challenges, we propose an end-to-end model with Learnable Embedding and capture Multidimensional Features (LEMF). LEMF can directly handle real-world time series with missing values. We utilize the LE module to extract richer temporal information, compensating for the limitations of missing data. The MF module can extract features related to the relationships between variables. We leverage these hidden representations for intention recognition, which is the time series classification task. We thoroughly evaluate our model on a self-constructed intention dataset. Compared to baseline model, the LEMF model achieved an average of 10% higher accuracy at each missing ratio. Additionally, we validate the model’s generalization capabilities on two real-world datasets. Our model also shows optimal or suboptimal performance.

A highly efficient combustion chamber is always desired for high performance from jet engines/rocket engines. This paper presents the novel numerical analysis method for optimizing the combustion characteristics of methane (CH₄) in an annular combustion chamber, achieving a maximum exit velocity nearly Mach 5. The velocity achieved is 1650 m/s, which is approximately 5 times of Mach number. The dimension of combustion chamber, length is 100 mm, diameter is 60 mm. Pre-combustion and post-combustion chamber length is 30 mm and 45 mm respectively. The port diameter is 16.5 mm and 4 injectors are used in this case. The main purpose of this paper is to investigate the optimize the combustion of solid fuel and air and justify the numerical model by using a 3D RANS simulation.

This paper is the first part of article series devoted to the computational study of thick composite panels buckling under compressive and shear loads taking into account through-the-thickness shear strains. In the first part of the study, an approximation is carried out taking into account the numerical solutions of the buckling problem. The first part presents a numerical study of orthotropic composite panels of a wide-body aircraft wing of large thicknesses, during which analytical dependencies are derived that determine the critical force for buckling under compressive and shear loads, taking into account through-the-thickness shear strains.

To determine the critical forces at which the panel buckles, the authors used a numerical modeling approach using the Finite Element Method (FEM) and Bubnov-Galerkin method (a method of aircraft structural mechanics). For this purpose, shell models of wing skin panels with orthotropic composite lay-up were made using a layer-by-layer modeling approach. A review of existing analytical dependencies for determining the critical forces for buckling of composite panels taking into account the through-the-thickness shear strains during compression was also carried out.

After validating the computational models, the authors conducted a series of virtual tests and analytical calculations for panels with different aspect ratios and thicknesses ranging from 1.8 mm to 24 mm in 2 mm increments. Based on the data obtained, the influence of through-the-thickness shear strains under compressive and shear loads was studied empirically, and an analytical relationship was obtained for assessing buckling of composite panels of large thicknesses under shear load.

The scientific novelty of this study is the identification of an empirical relationship for problems of composite panels of large thicknesses buckling under the influence of shear load, taking into account through-the-thickness shear strain.