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By using an array of pressure sensors distributed on the surface of an aircraft to measure the pressure of each port, the flush airdata sensing (FADS) system is widely applied in many modern aircraft and unmanned aerial vehicles (UAVs). Normally, the pressure transducers of the FADS system should be mounted on the leading edge of the aircraft, where they are sensitive to changes in pressure. For UAVs, however, the leading edge of the nose and wing may not be available for pressure transducers. In addition, the number of transducers is limited to 8–10, making it difficult to maintain accuracy in the normal method for FADS systems. An FADS system model for an unmanned flying wing was developed, and the pressure transducers were all located outside the regions of the leading edge areas. The locations of the transducers were selected by using the mean impact value (MIV), and ensemble neural networks were developed to predict the airdata with a very limited number of transducers. Furthermore, an error detection method was also developed based on artificial neural networks and random forests. The FADS system model can accurately detect the malfunctioning port and use the correct pressure combination to predict the Mach number, angle of attack, and angle of sideslip with high accuracy.

Additional file 2: Table S2. High-throughput sequencing profile of Small RNA.

Additional file 1: Table S1. Primers used for reverse transcription and quantitative PCR.

Icing phenomena are one of the hot issues in the aviation field, which has attracted the attention of many manufacturers. The physical process of water film flow determines the position and amount of icing. In this paper, the flow process of water film on a rough surface is studied. An experimental platform was built in a wind tunnel, and the digital image processing (DIP) technology was used to measure the water film flow. The water film flow under different roughness conditions of the plate was obtained in the experiments. The correction model of interfacial shear coefficient is established, and the influence of roughness on water film flow is deduced. The relationship obtained in this paper can provide data support for the study of gas-water coupled flows on rough surfaces.

Due to the limitations of impedance matching and attenuation matching, carbon nanotubes (CNTs) employed alone have a weak capacity to attenuate electromagnetic wave (EMW) energy. In this work, B and N co-doped CNTs with embedded Ni nanoparticles (Ni@BNCNTs) are fabricated via an in situ doping method. Compared with a sample without B doping, Ni@BNCNTs demonstrate a superior EMW absorption performance, with all minimum reflection loss values below −20 dB, even at a matching thickness of 1.5 mm. The experimental and theoretical calculation results demonstrate that B doping increases conduction and polarization relaxation losses, as well as the impedance matching characteristic, which is responsible for the enhanced EMW absorption performance of Ni@BNCNTs.