A low-temperature-resistant and high-strength stainless-steel jacket is a key component in the superconducting magnet of a fusion reactor.The development of cryogenic structural materials with high strength and toughn...A low-temperature-resistant and high-strength stainless-steel jacket is a key component in the superconducting magnet of a fusion reactor.The development of cryogenic structural materials with high strength and toughness poses a challenge for the future development of high-field superconducting magnets in fusion reactors.The yield strength of the International Thermonuclear Experimental Reactor developed for low-temperature structural materials at 4.2K is below 1100MPa,which fails to meet the demand for structural components with yield strengths exceeding 1500MPa at 4.2K in the future fusion reactors.CHSN01(formerly N50H),which is a low-temperature structural material developed in China,exhibits exceptional strength and toughness,thereby making it highly promising for practical applications.Recently,a 30 t jacket measuring approximately 5000m in total length was produced.Its low-temperature mechanical properties were tested using a sampling method to ensure compliance with application requirements.This paper presents the experimental data of the CHSN01 jacket and tests of the physical properties of the material in the temperature range of 4–300 K.The physical properties were unaffected by magnetic field.Furthermore,this paper discusses the feasibility of employing CHSN01 as a cryogenic structural material capable of withstanding high magnetic fields in next-generation fusion reactors.展开更多
珞珈二号01星的高分辨率Ka频段合成孔径雷达(synthetic aperture radar,SAR)为地表水体的精确监测提取提供了新数据源,但其毫米波雷达在精确刻画水体的同时,也引入了较多的地物信息干扰,对SAR的水体识别提出了更高要求。为应对这一挑战...珞珈二号01星的高分辨率Ka频段合成孔径雷达(synthetic aperture radar,SAR)为地表水体的精确监测提取提供了新数据源,但其毫米波雷达在精确刻画水体的同时,也引入了较多的地物信息干扰,对SAR的水体识别提出了更高要求。为应对这一挑战,提出了一种适用于高分辨率Ka频段SAR影像的KWEnet水体范围提取方法(the improved U-Net model for water extraction based on Ka-band SAR images),该方法在U-Net模型的上采样过程中增加了注意力机制,实现对特征图的加权,强化了水体信息的权重,减少对建筑物阴影等干扰特征的关注。将该方法应用于海河“23·7”流域性特大洪水事件,结果表明:KWEnet的F1分数(F1)、总体分类精度(overall accuracy,OA)以及交并比(intersection over union,IOU)分别达到95.6%、96.2%和91.5%,且在提取连通水体、减少漏提及剔除无关地物干扰等方面表现优异,对于星载Ka SAR的水体识别、洪涝灾害的监测和地表水资源的利用等具有重要意义。展开更多
基金supported in part by the National Natural Science Foundation of China(No.12305196)Anhui Provincial Natural Science Foundation(No.2308085QA23)+1 种基金Open Fund of Magnetic confinement Fusion Laboratory of Anhui Province(No.2023AMF03003)Science Foundation of Institute of Plasma Physics,Chinese Academy of Sciences(No.DSJJ-2024-10).
文摘A low-temperature-resistant and high-strength stainless-steel jacket is a key component in the superconducting magnet of a fusion reactor.The development of cryogenic structural materials with high strength and toughness poses a challenge for the future development of high-field superconducting magnets in fusion reactors.The yield strength of the International Thermonuclear Experimental Reactor developed for low-temperature structural materials at 4.2K is below 1100MPa,which fails to meet the demand for structural components with yield strengths exceeding 1500MPa at 4.2K in the future fusion reactors.CHSN01(formerly N50H),which is a low-temperature structural material developed in China,exhibits exceptional strength and toughness,thereby making it highly promising for practical applications.Recently,a 30 t jacket measuring approximately 5000m in total length was produced.Its low-temperature mechanical properties were tested using a sampling method to ensure compliance with application requirements.This paper presents the experimental data of the CHSN01 jacket and tests of the physical properties of the material in the temperature range of 4–300 K.The physical properties were unaffected by magnetic field.Furthermore,this paper discusses the feasibility of employing CHSN01 as a cryogenic structural material capable of withstanding high magnetic fields in next-generation fusion reactors.
文摘珞珈二号01星的高分辨率Ka频段合成孔径雷达(synthetic aperture radar,SAR)为地表水体的精确监测提取提供了新数据源,但其毫米波雷达在精确刻画水体的同时,也引入了较多的地物信息干扰,对SAR的水体识别提出了更高要求。为应对这一挑战,提出了一种适用于高分辨率Ka频段SAR影像的KWEnet水体范围提取方法(the improved U-Net model for water extraction based on Ka-band SAR images),该方法在U-Net模型的上采样过程中增加了注意力机制,实现对特征图的加权,强化了水体信息的权重,减少对建筑物阴影等干扰特征的关注。将该方法应用于海河“23·7”流域性特大洪水事件,结果表明:KWEnet的F1分数(F1)、总体分类精度(overall accuracy,OA)以及交并比(intersection over union,IOU)分别达到95.6%、96.2%和91.5%,且在提取连通水体、减少漏提及剔除无关地物干扰等方面表现优异,对于星载Ka SAR的水体识别、洪涝灾害的监测和地表水资源的利用等具有重要意义。
