LI Zhen-lei, CHEN Dong, KANG Jian, YUAN Guo. Effect of Online-Cooling on Microstructure and Mechanical Properties of Hot-Rolled L360 Steel Pipe[J]. Journal of Northeastern University Natural Science, 2018, 39(11): 1588-1592.
[1]王国栋,王昭东,刘振宇,等.基于超快冷的控轧控冷装备技术的发展[J].中国冶金,2016,26(10):9-17.(Wang Guo-dong,Wang Zhao-dong,Liu Zhen-yu,et al.Development of TMCP technology based on ultra-fast cooling[J].China Metallurgy,2016,26(10):9-17.) [2]Wu D,Li Z,Lu H S.Effect of controlled cooling after hot roiling on mechanical properties of hot rolled TRIP steel[J].ISIJ International,2008,15(2):65-70. [3]王国栋.控轧控冷技术的发展及在钢管轧制中应用的设想[J].钢管,2011,40(2):1-8.(Wang Guo-dong.Development of TMCP and envisaged application to steel tube rolling[J].Steel Pipe,2011,40(2):1-8.) [4]Hua W U.Microstructure and properties of 22Mn2SiVBS seamless steel pipe treated by controlling cooling after hot rolling[J].Materials for Mechanical Engineering,2007,31(7):1-3. [5]Wang J Q,Atrens A,Cousens D R,et al.Microstructure of X52 and X65 pipeline steels[J].Journal of Materials Science, 1999,34(8):1721-1728. [6]Hillert M.Diffusion-controlled lengthening of Widmanstatten plates[J].Acta Materials,2003,51(7):2089-2095. [7]Huang B M,Yen H W,Ho D,et al.The influence of Widmansttten ferrite on yielding behavior of Nb-containing reinforcing steel bars[J].Scripta Materialia,2012,67(5):431-434. [8]Hu J,Du L X,Wang J J.Effect of cooling procedure on microstructures and mechanical properties of hot rolled Nb –Ti bainitic high strength steel[J].Materials Science and Engineering:A,2012,554:79-85. [9]Anelli E,Armengol M,Novelli P,et al.High strength steel pipes with excellent toughness at low temperature and sulfide stress corrosion cracking resistance:9598746[P].2017-07-11. [10]Liu L,Xiao H,Li Q,et al.Evaluation of the fracture toughness of X70 pipeline steel with ferrite-bainite microstructure[J].Materials Science and Engineering A,2017,688:388-395.(上接第1581页) [8]Shelhamer E,Long J,Darrell T.Fully convolutional networks for semantic segmentation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2017,39(4):640-651. [9]Shin H C,Roth H R,Gao M,et al.Deep convolutional neural networks for computer-aided detection:CNN architectures,dataset characteristics and transfer learning[J].IEEE Transactions on Medical Imaging,2016,35(5):1285-1298. [10]Kingma D P,Ba J.Adam:a method for stochastic optimization[C]// International Conference on Learning Representations.Amherst:UMASS,2015:1-13. [11]Srivastava N,Hinton G E,Krizhevsky A,et al.Dropout:a simple way to prevent neural networks from overfitting[J].Journal of Machine Learning Research,2014,15(1):1929-1958. [12]Dice L R.Measures of the amount of ecologic association between species[J].Ecology,1945,26(3):297-302. [13]Connelly K A,Detsky J S,Graham J J,et al.Multicontrast late gadolinium enhancement imaging enables viability and wall motion assessment in a single acquisition with reduced scan times[J].Journal of Magnetic Resonance Imaging,2009,30(4):771-777. [14]Hu H,Liu H,Gao Z,et al.Hybrid segmentation of left ventricle in cardiac MRI using Gaussian-mixture model and region restricted dynamic programming[J].Magnetic Resonance Imaging,2013,31(4):575-584. [15]Liu H,Hu H,Xu X,et al.Automatic left ventricle segmentation in cardiac MRI using topological stable-state thresholding and region restricted dynamic programming[J].Academic Radiology,2012,19(6):723-731.