In this study, a new R-δf-type welding window on charge parameters is constructed by determining the boundary conditions of the explosive ratio. The R-δf-type welding window synthetically considers the explosive pro...In this study, a new R-δf-type welding window on charge parameters is constructed by determining the boundary conditions of the explosive ratio. The R-δf-type welding window synthetically considers the explosive properties and material properties, and can quickly determine the explosive charge at different welding materials with different thickness. In order to test the practicability and accuracy of the R-δf-type welding window, 410S stainless steel and Q345R low alloy steel plates were explosively welded using 15 mm charge determined by the new window. Microstructures of the bonded sections were examined and then shear tests were carried out on the bonded specimens. Microstructural examination showed the joint interface was transformed from micro wavy to small wavy appearance without microstructure defects. Shear tests results showed inter inacial shear strength was much higher than that of the national first grade standard. So the R-δf-type welding window has strong practicability and accuracy and is helpful to the practical production and application of explosive welding composite materials.展开更多
Cloud detection and classification form a basis in weather analysis. Split window algorithm (SWA) is one of the simple and matured algorithms used to detect and classify water and ice clouds in the atmosphere using sa...Cloud detection and classification form a basis in weather analysis. Split window algorithm (SWA) is one of the simple and matured algorithms used to detect and classify water and ice clouds in the atmosphere using satellite data. The recent availability of Himawari-8 data has considerably strengthened the possibility of better cloud classification owing to its enhanced multi-band configuration as well as high temporal resolution. In SWA, cloud classification is attained by considering the spatial distributions of the brightness temperature (BT) and brightness temperature difference (BTD) of thermal infrared bands. In this study, we compare unsupervised classification results of SWA using the band pair of band 13 and 15 (SWA13-15, 10 and 12 μm bands), versus that of band 15 and 16 (SWA15-16, 12 and 13 μm bands) over the Japan area. Different threshold values of BT and BTD are chosen in winter and summer seasons to categorize cloud regions into nine different types. The accuracy of classification is verified by using the cloud-top height information derived from the data of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). For this purpose, six different paths of the space-borne lidar are selected in both summer and winter seasons, on the condition that the time span of overpass falls within the time ranges between 01:00 and 05:00 UTC, which corresponds to the local time around noon. The result of verification indicates that the classification based on SWA13-15 can detect more cloud types as compared with that based on SWA15-16 in both summer and winter seasons, though the latter combination is useful for delineating cumulonimbus underneath dense cirrus展开更多
基金supported by the National Natural Science Foundation of China(Grant No.51541112)
文摘In this study, a new R-δf-type welding window on charge parameters is constructed by determining the boundary conditions of the explosive ratio. The R-δf-type welding window synthetically considers the explosive properties and material properties, and can quickly determine the explosive charge at different welding materials with different thickness. In order to test the practicability and accuracy of the R-δf-type welding window, 410S stainless steel and Q345R low alloy steel plates were explosively welded using 15 mm charge determined by the new window. Microstructures of the bonded sections were examined and then shear tests were carried out on the bonded specimens. Microstructural examination showed the joint interface was transformed from micro wavy to small wavy appearance without microstructure defects. Shear tests results showed inter inacial shear strength was much higher than that of the national first grade standard. So the R-δf-type welding window has strong practicability and accuracy and is helpful to the practical production and application of explosive welding composite materials.
文摘Cloud detection and classification form a basis in weather analysis. Split window algorithm (SWA) is one of the simple and matured algorithms used to detect and classify water and ice clouds in the atmosphere using satellite data. The recent availability of Himawari-8 data has considerably strengthened the possibility of better cloud classification owing to its enhanced multi-band configuration as well as high temporal resolution. In SWA, cloud classification is attained by considering the spatial distributions of the brightness temperature (BT) and brightness temperature difference (BTD) of thermal infrared bands. In this study, we compare unsupervised classification results of SWA using the band pair of band 13 and 15 (SWA13-15, 10 and 12 μm bands), versus that of band 15 and 16 (SWA15-16, 12 and 13 μm bands) over the Japan area. Different threshold values of BT and BTD are chosen in winter and summer seasons to categorize cloud regions into nine different types. The accuracy of classification is verified by using the cloud-top height information derived from the data of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). For this purpose, six different paths of the space-borne lidar are selected in both summer and winter seasons, on the condition that the time span of overpass falls within the time ranges between 01:00 and 05:00 UTC, which corresponds to the local time around noon. The result of verification indicates that the classification based on SWA13-15 can detect more cloud types as compared with that based on SWA15-16 in both summer and winter seasons, though the latter combination is useful for delineating cumulonimbus underneath dense cirrus
