Aerospace Systems最新文献

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.

This paper presents an image-feature-aware (IFA) planner for quadrotors, which integrates image feature tracking into its path-planning framework. The IFA-planner aims to improve the visual localization performance of quadrotors in multifarious environments where feature points may be sparse or diverse. Unlike traditional methods that decouple visual localization and path planning, the IFA-planner adaptively identifies and tracks feature-rich spatial units, called anchors, along a feasible path. The anchors provide additional feature points to the visual localization module, especially in scenarios with sparse or uneven features, thus enhancing localization robustness. Via clustering-based method, the anchor selection can handle different feature point distributions without manual tuning. Moreover, a detachment prediction mechanism is incorporated to convert the selected anchors into yaw constraints and update them according to the quadrotor’s predicted state. This mechanism ensures the environmental adaptability of the anchors and avoids sudden feature changes. The effectiveness of the IFA-planner is demonstrated in simulation experiments. The source code has been released at https://github.com/ximuzi2023/IFA-planner.

Microburst is a common low-level wind shear weather, and it seriously threatens the safety of civil aviation flights. It is characterized by suddenness, short duration, small scale and large intensity, which leads to difficulties in accurately obtaining real data, in real-time assessing the degree of harm. In this paper, based on the characteristics of microburst, according to computational fluid dynamics, taking into account the changes of temperature and pressure with height, establish a three-dimensional wind field simulation model, and verify the validity of the model by experimental data. Using the F-factor, construct the quantitative model of each position in the wind shear region, and analyze the danger degree of the micro downwash storm flow. Investigate the influence of inlet velocity, inlet height and inlet diameter on the hazard radius, and the simulation results show that the hazard radius increases logistically with the decrease of altitude, and when the inlet velocity increases by 5 m/s or the inlet height increases by 80 m, the hazard radius increases by about 10% on average. The method of this paper can provide a new way to quantitatively analyze the wind field characteristics of micro downburst storms.