Fabrics are widely applied in various fields, such as body armor, aerospace industry and military equipment. This paper reports the semi-blunt puncture behavior of fabrics impregnated with a shear thickening fluid (STF), which is a dispersion system of nano silica/polyethylene glycol (SiO₂/PEG). The rheological properties and microstructure of the STF were tested to evaluate the influence of SiO₂ particle size and additives (graphene nanoplatelets) on the puncture behavior of the final fabrics. The surface characteristics of neat and STF-treated fabrics were separately measured by field emission scanning electron microscopy (FESEM), which helps study the damage morphology and mechanism of the fabric. The surface characteristics of the silica nanoparticles and additives were also measured by transmission electron microscopy (TEM). The results demonstrated that the puncture behavior of the woven fabric was significantly enhanced due to the presence of STF. Moreover, the presence of additive GNPs induced a relatively lower shear thickening phenomenon, while a significant enhancement in the semi-blunt puncture behavior of the woven fabric was observed.

Large-scale low Earth orbit (LEO) remote satellite constellations have become a brand new, massive source of space data. Federated learning (FL) is considered a promising distributed machine learning technology that can communicate optimally using these data. However, when applying FL in satellite networks, it is necessary to consider the unique challenges brought by satellite networks, which include satellite communication, computational ability, and the interaction relationship between clients and servers. This study focuses on the siting of parameter servers (PSs), whether terrestrial or extraterrestrial, and explores the challenges of implementing a satellite federated learning (SFL) algorithm equipped with client selection (CS). We proposed an index called “client affinity” to measure the contribution of the client to the global model, and a CS algorithm was designed in this way. A series of experiments have indicated the advantage of our SFL paradigm—that satellites function as the PS—and the availability of our CS algorithm. Our method can halve the convergence time of both FedSat and FedSpace, and improve the precision of the models by up to 80%.

This paper aimed to reveal the low-velocity impact responses characteristics and failure mechanism of 3-D braided composites with experimental and frequency domain analysis method, respectively. The low-velocity impact tests were carried out by Instron® 9250 drop-weight instrument with five different impact velocities from 1 m/s to 6 m/s. The results showed that the peak load and absorbed energy increased with the increase of impact velocity. The load–time curves which were in time domain were transformed into frequency domain with Hilbert–Huang Transform (HHT) method. Combined the failure morphologies of 3-D braided composites with frequency domain analysis results, it could be precisely found out the failure mechanism of 3-D braided composites. At the impact velocity of 1 m/s, the 3-D braided composites only had elastic deformations. With the increase of impact velocity, resin crack was the main failure mode of 3-D braided composites. The frequency of impact stress waves which caused the elastic deformation and resin crack mainly located at 0–10 kHz and 60 kHz. When the impact velocity increased to 6 m/s, fiber tows breakage was the main failure mode, and the frequency of impact stress wave located at 15–20 kHz.