A Deep Learning-Based Algorithm for Identifying Precipitation Clouds Using Fengyun-4A Satellite Observation Data.

Rapid and accurate identification of precipitation clouds from satellite observations is essential for the research of quantitative precipitation estimation and precipitation nowcasting. In this study, we proposed a novel Convolutional Neural Network (CNN)-based algorithm for precipitation cloud identification (PCINet) in the daytime, nighttime, and nychthemeron. High spatiotemporal and multi-spectral information from the Fengyun-4A (FY-4A) satellite is utilized as the inputs, and a multi-scale structure and skip connection constraint strategy are presented in the framework of the algorithm to improve the precipitation cloud identification. Moreover, the effectiveness of visible/near-infrared spectral information in improving daytime precipitation cloud identification is explored. To evaluate this algorithm, we compare it with five other deep learning models used for image segmentation and perform qualitative and quantitative analyses of long-time series using data from 2021. In addition, two heavy precipitation events are selected to analyze the spatial distribution of precipitation cloud identification. Statistics and visualization of the experiment results show that the proposed model outperforms the baseline models in this task, and adding visible/near-infrared spectral information in the daytime can effectively improve model performance. More importantly, the proposed model can provide accurate and near-real-time results, which has important application in observing precipitation clouds.

Effect of Femtosecond Laser Processing Parameters on the Ablation Microgrooves of RB-SiC Composites.

Because of the high hardness, brittleness, and anisotropy of reaction-bonded silicon carbide composites (RB-SiC), it is challenging to process high-quality textures on their surfaces. With the advantages of high processing accuracy and low processing damage, femtosecond laser processing is the preferred technology for the precision processing of difficult-to-process materials. The present work used a femtosecond laser with a linear scanning path and a spot diameter of 18 µm to process microgrooves on RB-SiC. The influence of different processing parameters on the microgroove profile, dimensions, and ablation rate (AR) was investigated. The ablation width Wa and average ablation depth Da of microgrooves were evaluated, and the various patterns of varying processing parameters were obtained. A model for Wa prediction was developed based on the laser fluence within the finite length (FL). As a result, the experimental values were distributed near the prediction curve with a maximum error of 20.4%, showing an upward trend of gradually decreasing increments. For a single pass, the AR value was mainly determined by the laser energy, which could reach the scale of 106 µm3/s when the laser energy was greater than 50 µJ. For multiple passes, the AR value decreased as the number of passes increased and it finally stabilized. The above research will provide theoretical and experimental support for the high-quality and efficient processing of RB-SiC surface textures.

Numerical simulation of femtosecond laser ablation of quartz glass and silicon nitride.

The ablation threshold and depth models were established based on the electron density evolution equation of dielectric and ionization theory. The volume model was then deduced, and the models were validated. For quartz glass and silicon nitride, the dependences of the threshold with pulse duration, ablation depth, and volume with fluence were analyzed. Also, the relations of scallop height and scanning velocity were predicted. The results show that the thresholds of quartz glass at durations of 12, 35, and 220 fs were 3.3, 2.9, and 2.3J/cm2, respectively, while the thresholds of silicon nitride at the same durations were 2.0, 1.8, and 1.4J/cm2, respectively. The ablation depth of quartz glass decreased with the increase of duration when the fluence deviated from the threshold. The depth of silicon nitride was opposite to it, and the ablation volume of silicon nitride was larger than that of quartz glass in the same condition. When the scanning velocity and fluence were determined, the scallop height decreased with the increase of duration. However, when the velocity and duration were determined, the scallop height increased with the increase of fluence. The shorter the duration was, the greater the variation of the scallop height.

Accelerated decline of snow cover in China from 1979 to 2018 observed from space.

Snow cover is an important indicator of climate change. Variations of snow integrate the competing effect of increasing temperature and precipitation. In this study, based on Theil-Sen Median (TSM) and Mann-Kendall (M-K) methods, observational evidence from space was used to investigate the variation of snow parameters in China from 1979 to 2018, and some meaningful conclusions were found. (1) The downward trend of snow depth (SD) with a median of -0.02 cm/year was generally found in the high altitude mountains, and the upward trend of SD with a median of 0.01 cm/year occurs in the plains. A widespread and accelerated decrease of SD was observed in the latest period (2009-2018) in NC and NX. (2) The mean annual areas with snow cover days (SCDs) greater than 150 days (d) accounted for 17.8%, 24.73% and 38.14% in NC, NX and QTP. SCDs in NC and Northern QTP were widely reduced, but the longest snow season with more than eight months is still maintained on QTP. (3) The downward trend of snow storage (SS) was found in all three snow areas. The difference of snow phenology is reflected in the slowest accumulation and melting rate of SS on QTP; the largest peak value of SS and the shortest snow season in NC; the slow accumulation and rapid melting of snow in the NX, and the peak value is achieved at the latest. The trend of maximum temperature was judged as the most important factor affecting the change of SD, while longitude and latitude are closely related to the change of SCD.

Microstructure and Wear Property of ZrO2-Added NiCrAlY Prepared by Ultrasonic-Assisted Direct Laser Deposition.

For improving the wear properties of NiCrAlY, the 10 wt %, 20 wt % and 30 wt % ZrO2-added NiCrAlY samples were prepared by ultrasonic-assisted direct laser deposition, respectively. The results showed that the ultrasonic-assisted direct laser deposition can realize the ZrO2-added NiCrAlY preparation. Furthermore, due to the cavitation effect and agitation of the ultrasound in the molten pool, ultrasonic-assisted could make the upper surface of the samples smoother and flatter, and it also improved the microstructural homogeneity. The microstructure was mainly composed of columnar dendrites, and most of ZrO2 particles were located in the intergranular regions. The principal phase constituents were found to contain γ-Ni and t-NiZr2, and the amorphous (Ni, Zr) intermetallic phase generated, because of more rapid solidification after ultrasound assisted. The microhardness was improved slightly with the increase of ZrO2 contents, rising from 407.9 HV (10% ZrO2) to 420.4 HV (30% ZrO2). Correspondingly, wear mass loss was decreased with the maximum drop 22.7% of 30% ZrO2 compared to that of 10% ZrO2, and wear mechanisms were mainly abrasive wear with slightly adhesive wear. After applying ultrasound, the oxide islands in samples disappeared, and more ceramic particles were retained. Thus, the hardness and wear performance of the samples were improved.

Faceted and Circular Droplet Spreading on Hierarchical Superhydrophobic Surfaces.

Bouncing of water droplets on the post-built superhydrophobic surfaces was studied. The topography of the surfaces was constituted by PDMS conical posts decorated with ZnO nanoparticles. Droplet impact on surface topographies built of posts with varied configuration and separation was studied under different Weber numbers. Faceted spreading and retraction of droplets were observed. Square-, pentagon-, and hexagon-shaped droplets were registered. It was shown that the nature of droplet spreading depended on both the Weber number and the topography of the post arrays. Even bouncing under small Weber numbers We ≅ 6.5 resulted in the Cassie-Wenzel transitions, starting from the area adjacent to the axis of droplets, and the area exposed to the wetting transitions scaled as [Formula: see text]. During spreading, two main stages were recorded as the kinematic (inertial) stage and the viscous stage. The viscous stage, in turn, appeared as a consequence of two substages governed by various time scaling laws. The faceted triple line was observed for the Cassie-like retraction of droplets.