The volume fraction and morphology of the TCP-phase formed in two kinds of Ni- Mo-Cr-Re superalloys under different heat treatment conditions were investigated in this paper. In Re-5% alloy, with increasing of the hea...The volume fraction and morphology of the TCP-phase formed in two kinds of Ni- Mo-Cr-Re superalloys under different heat treatment conditions were investigated in this paper. In Re-5% alloy, with increasing of the heat treatment temperature and prolonging the holding time, the volume fraction of TCP-phase decreased and the TCP-phase size increased. At relatively lower temperature, the TCP-phase prefers to present in the dendrite cores. In Re-10% alloy, the volume fraction and size have the same change tendency as that of in Re-5% alloy, but the morphology will change from needle-like and block-like to sphere when the temperature increases. The TCP-phases formed in these two Ni-Mo-Cr-Re alloys are σ and P phase.展开更多
Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and management.in this study,we developed an automated an...Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and management.in this study,we developed an automated and refined wetland mapping framework integrating training sample migration method,supervised machine learning and knowledge-driven rules using Google Earth Engine(GEE)platform and open-source geospatial tools.We applied the framework to temporally dense Sentinel-1/2 imagery to produce annual refined wetland maps of the Dongting Lake Wetland(DLW)during 2015-2021.First,the continuous change detection(CCD)algorithm was utilized to migrate stable training samples.Then,annual 10 m preliminary land cover maps with 9 classes were produced using random forest algorithm and migrated samples.Ultimately,annual 10 m refined wetland maps were generated based on preliminary land cover maps via knowledge-driven rules from geometric features and available water-related inventories,with Overall Accuracy(OA)ranging from 81.82%(2015)to 93.84%(2020)and Kappa Coefficient(KC)between 0.73(2015)and 0.91(2020),demonstrating satisfactory performance and substantial potential for accurate,timely and type-refined wetland mapping.Our methodological framework allows rapid and accurate monitoring of wetland dynamics and could provide valuable information and methodological support for monitoring,conservation and sustainable development of wetland ecosystem.展开更多
基金the financial support from the National High Magnetic Field Laboratory under NSF DMR-0084173
文摘The volume fraction and morphology of the TCP-phase formed in two kinds of Ni- Mo-Cr-Re superalloys under different heat treatment conditions were investigated in this paper. In Re-5% alloy, with increasing of the heat treatment temperature and prolonging the holding time, the volume fraction of TCP-phase decreased and the TCP-phase size increased. At relatively lower temperature, the TCP-phase prefers to present in the dendrite cores. In Re-10% alloy, the volume fraction and size have the same change tendency as that of in Re-5% alloy, but the morphology will change from needle-like and block-like to sphere when the temperature increases. The TCP-phases formed in these two Ni-Mo-Cr-Re alloys are σ and P phase.
基金supported by the National Natural Science Foundation of China(grant numbers 42071393,U1901219 and U21A2022).
文摘Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and management.in this study,we developed an automated and refined wetland mapping framework integrating training sample migration method,supervised machine learning and knowledge-driven rules using Google Earth Engine(GEE)platform and open-source geospatial tools.We applied the framework to temporally dense Sentinel-1/2 imagery to produce annual refined wetland maps of the Dongting Lake Wetland(DLW)during 2015-2021.First,the continuous change detection(CCD)algorithm was utilized to migrate stable training samples.Then,annual 10 m preliminary land cover maps with 9 classes were produced using random forest algorithm and migrated samples.Ultimately,annual 10 m refined wetland maps were generated based on preliminary land cover maps via knowledge-driven rules from geometric features and available water-related inventories,with Overall Accuracy(OA)ranging from 81.82%(2015)to 93.84%(2020)and Kappa Coefficient(KC)between 0.73(2015)and 0.91(2020),demonstrating satisfactory performance and substantial potential for accurate,timely and type-refined wetland mapping.Our methodological framework allows rapid and accurate monitoring of wetland dynamics and could provide valuable information and methodological support for monitoring,conservation and sustainable development of wetland ecosystem.
