Aerospace Systems最新文献

Digital Image Correlation (DIC) is a vital optical measurement technique that finds diverse applications in the domain of mechanics of materials. In aerospace applications, DIC has excellent scope in structural health monitoring of aircraft components. Aircraft wings, one of the critical components are subjected to different loads during flight. Ground testing and In-flight testing of wings can benefit substantially by DIC monitoring. DIC can be utilized to analyze the time-based variation in the speckle pattern or grid, applied to the wing’s surface. High-resolution images processed through a suitable correlation software helps decipher the data into stress and strain contours. Thus, any potential material failure or component defects can be identified. DIC also finds a role in flutter analysis, enabling the scrutiny of wing vibrations and deformations. In this review, the applications of DIC in analysis of aircraft components has been taken up, as in-flight structural health monitoring is a critical activity for a safe flight.

Aerial Gliding Vehicles (AGVs) play a crucial role in military operations owing to their versatile and multipurpose capabilities. Achieving accurate modeling of AGVs is paramount for understanding their behavior and optimizing performance. While nonlinear models excel in capturing intricate phenomena, their complexity and computational demands make them less suitable for control system design. Hence, the utilization of linear models becomes imperative, offering a more comprehensible depiction of AGV dynamics and facilitating effective control system analysis and design. This study aims to develop a precise linear model for AGVs, providing a clear and interpretable framework for analysis and control system development. The constructed linear model serves as the foundation for devising various control strategies, significantly enhancing our comprehension of AGV behavior. Moreover, a comprehensive investigation into the AGV’s actuation system is conducted, employing advanced system identification techniques to establish an accurate actuation model. This phase is critical for ensuring the precise and efficient operation of the control system. The research encompasses the design and evaluation of two distinct AGV control strategies. Firstly, the Modified Proportional-Integral-Derivative (PI-D) controller, a conventional approach widely employed in control systems, serves as a stable benchmark for comparison. Secondly, the innovative Fuzzy-PI-D (F-PI-D) controller is introduced, harnessing fuzzy logic to augment control accuracy and responsiveness, particularly advantageous for complex systems like AGVs. To validate the performance of these control strategies, the study adopts the robust Processor in the Loop (PIL) methodology, integrating LabVIEW and an embedded device to conduct reliable testing and verification of control systems in a simulated environment. PIL offers the distinct advantage of evaluating control strategies under diverse conditions without the necessity of costly and hazardous real-world flight tests. Simulation outcomes furnish valuable insights into the efficacy of these control strategies. Significantly, the F-PI-D controller emerges as the preferred choice for enhancing AGV flight stability, precision, and responsiveness, thus contributing to the advancement of AGV control systems and their utility in military operations.

The stability criteria of any fin-stabilized flying object are a decisive metric in evaluating its overall performance and results in mission success. Flight stability depends on many parameters such as body configuration, the center of gravity location, atmospheric conditions, and flight manoeuvres. These manoeuvres are needed for better target interception especially for moving targets located at short ranges, resulting in high frequencies either in pitch or yaw directions. This study examines the impact of body pitch frequency on the stability of a supersonic fin-stabilized object. Time-dependent numerical simulations are implemented to model the unsteady flow field induced by a simple harmonic motion in the case study missile. The missile’s tail section dominates the lift force generated compared to the forebody, resulting in a downstream shift of the missile’s center of pressure and, consequently, an increase in the static stability margin as the pitching frequency increases. However, pitch-damp aerodynamic derivatives remain unchanged at various pitching frequencies, indicating frequency independence. The validity of the results is confirmed compared with wind tunnel data.

The objective of the paper is to explore the fields of propulsion for rockets and defence systems to meet the increasing demands for cost-effectiveness and faster and friendly manufacturing processes to increase the efficiency of the burn time/rate of solid rocket motors. This particular research includes the use of powerful machine learning algorithms applied on the burn rate dataset to predict the best burn rate. The main focus of this particular research is based on the burning rate study which has been carried out at ambient and different pressures of 2.068 MPa, 4.760 MPa and 6.895 MPa with the use of binder as Hydroxyl-Terminated Polybutadiene, oxidizer as Ammonium Perchlorate and a catalyst as Iron Oxide. Two types of models are designed and created to predict the best burn rate from the experiments conducted namely; Empirical Mathematical Model and Machine Learning Regression. Empirical modelling gave an accuracy of 47% while Machine Learning Regression gave a prediction accuracy of nearly 99%.

This article presents the synthesis of a dynamic output feedback controller for a satellite orbital system confronted with uncertainties. The investigated method transforms the closed-loop system, synthesized by the controller, into an (alpha )-strictly negative-imaginary system. It utilizes the DC-loop gain condition associated with negative-imaginary systems theory to demonstrate robust stability of the satellite orbital system in the presence of uncertainties. Furthermore, the synthesized negative-imaginary closed-loop system exhibits notable time-domain performance. The numerical simulation outcomes presented in this article validate the investigated synthesis method.

Composite lattice anisogrid adapters are highly favored in space rocketry design, serving as crucial interface structures between rocket stages or between the payload and its supporting structure. Their unique structural configuration allows them to withstand significant weight loads without succumbing to buckling. However, optimizing their design parameters could further enhance their strength and efficiency. Particularly, reinforcing the lower hoop ribs in a conical lattice adapter can substantially enhance its strength under axial compressive loads, thus preventing buckling. In this study, we begin by presenting a finite-element model of a lattice adapter featuring helical ribs that follow geodesic paths. To validate the model's accuracy, experimental prototypes and finite-element models from previous research are utilized. Subsequently, a neural network model is trained using the dataset generated from finite-element analysis results. This neural network model aims to predict, explore, and optimize the impact of lower hoop ribs' thicknesses on the critical axial buckling load of the adapter. The analysis ultimately confirms that an adapter designed with optimized ribs demonstrates a remarkable 51% increase in load capacity before buckling compared to an adapter designed with uniform ribs. This underscores the significance of optimizing design parameters for enhancing structural performance in space rocketry applications.

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Controlled flight into terrain accidents pose a significant threat to aviation safety, emphasizing the need for effective automatic ground collision avoidance system (Auto GCAS). However, the diversity and complexity of missions present considerable challenges to aircraft collision avoidance control. This paper proposes an approach for trajectory prediction based on the model predictive control (MPC) technique. Different from previous methods that rely on predefined fixed trajectories, the proposed approach incorporates constraints of aircraft state and actual terrain to generate an optimal trajectory. The safety and effectiveness of the method are demonstrated through integrating the trajectory prediction algorithm into the Auto GCAS system. The simulation results show that the MPC-based Auto GCAS can achieve optimal collision avoidance outcomes aligned with the aircraft's performance and mission needs.

The aircraft wing is a complex structure consisting of many joined components. Because of the inevitable variability of the component shapes, different deviations may occur in the joining process including unreduced gaps between parts which can negatively affect the quality of further assembly. When developing the assembly process, the influence of these variations can be taken into account by considering the initial gap between the parts. For the variation analysis of the aircraft assembly process, a large set of random initial gaps between the parts is needed. To get this set without initial gap measurements it is proposed to use the method of modeling the initial gap based on the mode shape decomposition. The initial gap is represented as a sum of orthonormal mode shapes with random coefficients. This paper describes the method for estimating parameters and generating initial gap samples for such cases without initial gap measurements. The application of this method is illustrated for the wing assembly process. The effectiveness of the initial gap modeling based on residual gap measurements is studied and the application of this initial gap model for fastening pattern optimization is performed.

Synthetic jets (SJs) are becoming increasingly popular in aerospace engineering due to their potential applications in flow mixing enhancement, boundary layer control, and thermal load reduction. These pulsating jets involve the periodic motion of fluid in and out of a cavity through an orifice generated by a vibrating diaphragm at the cavity base. SJs are unique because they comprise working fluid and do not require an external fluid source, setting them apart from conventional flow control techniques. Although the net mass flux is zero in a complete cycle, there is a finite net momentum flux due to the imbalanced flow conditions across the orifice, and hence SJs are also known as Zero Net Mass Flux (ZNMF) jets. Numerous experimental and numerical studies have evaluated the efficacy of SJs in controlling the flow and heat transfer characteristics under various conditions, including quiescent and cross-flow situations. This review provides a comprehensive overview of the progress in synthetic jet applications in the last 40 years, specifically focusing on their potential use in flow control, heat transfer, and related applications in aerospace engineering. The strengths and limitations of SJs are discussed, and critical areas are identified for future research and development, including further optimization and refinement of these unique jets.

Mode composition beamforming (MCB) is a frequency-domain rotating beamforming method for rotating acoustic source localization. Compared with other rotating beamforming methods, MCB has both wide applicability and high computational efficiency. The expression for MCB in literature is however not suitable for the application of deconvolution algorithms, which limits further improvements of dynamic range and spatial resolution of MCB. In this work, application of deconvolution algorithms to MCB is investigated. Firstly, the expression of MCB is transformed into a matrix form. Then the deconvolution algorithms of MCB, including DAMAS and CLEAN-SC, are derived based on the matrix form of MCB. Nextly the deconvolution algorithms of MCB are verified through a benchmark simulation case. Lastly deconvolution algorithms of MCB are applied in a phased array measurement for the rotor of an unmanned aerial vehicle to improve the dynamic range and spatial resolution of rotating source localization.