Cu-4.7%Sn （mass fraction） alloy plate was prepared by the self-developed two-phase zone continuous casting （TZCC） process. The relationship between process parameters of TZCC and surface quality of the alloy plate...Cu-4.7%Sn （mass fraction） alloy plate was prepared by the self-developed two-phase zone continuous casting （TZCC） process. The relationship between process parameters of TZCC and surface quality of the alloy plate was investigated. The microstructure and mechanical properties of the TZCC alloy plate were analyzed. The results show that Cu-4.7%Sn alloy plate with smooth surface can be obtained by means of reasonable matching the entrance temperature of two-phase zone mold and the continuous casting speed. The microstructure of the TZCC alloy is composed of grains-covered grains, small grains with self-closed grain boundaries, columnar grains and equiaxed grains. Compared with cold mold continuous casting Cu-4.7%Sn alloy plate, the room temperature tensile strength and ductility of the TZCC alloy plate are greatly improved.展开更多
Microstructures of Cu-4.7Sn(%) alloys prepared by two-phase zone continuous casting(TZCC)technology contain large columnar grains and small grains.A compound grain structure,composed of a large columnar grain and at l...Microstructures of Cu-4.7Sn(%) alloys prepared by two-phase zone continuous casting(TZCC)technology contain large columnar grains and small grains.A compound grain structure,composed of a large columnar grain and at least one small grain within it,is observed and called as grain-covered grains(GCGs).Distribution of small grains,their numbers and sizes as well as numbers and sizes of columnar grains were characterized quantitatively by metallographic microscope.Back propagation(BP) artificial neural network was employed to build a model to predict microstructures produced by different processing parameters.Inputs of the model are five processing parameters,which are temperatures of melt,mold and cooling water,speed of TZCC,and cooling distance.Outputs of the model are nine microstructure quantities,which are numbers of small grains within columnar grains,at the boundaries of the columnar grains,or at the surface of the alloy,the maximum and the minimum numbers of small grains within a columnar grain,numbers of columnar grains with or without small grains,and sizes of small grains and columnar grains.The model yields precise prediction,which lays foundation for controlling microstructures of alloys prepared by TZCC.展开更多
基金Project(51374025) supported by the National Natural Science Foundation of ChinaProject(2014Z-05) supported by the State Key Laboratory for Advanced Metals and Materials,University of Science and Technology Beijing,ChinaProject(2152020) supported by the Beijing Natural Science Foundation,China
文摘Cu-4.7%Sn （mass fraction） alloy plate was prepared by the self-developed two-phase zone continuous casting （TZCC） process. The relationship between process parameters of TZCC and surface quality of the alloy plate was investigated. The microstructure and mechanical properties of the TZCC alloy plate were analyzed. The results show that Cu-4.7%Sn alloy plate with smooth surface can be obtained by means of reasonable matching the entrance temperature of two-phase zone mold and the continuous casting speed. The microstructure of the TZCC alloy is composed of grains-covered grains, small grains with self-closed grain boundaries, columnar grains and equiaxed grains. Compared with cold mold continuous casting Cu-4.7%Sn alloy plate, the room temperature tensile strength and ductility of the TZCC alloy plate are greatly improved.
基金financially supported by the National Key Research and Development Plan of China (No.2016YFB0301300)the National Natural Science Foundation of China (Nos.51374025,51674027 and U1703131)the Beijing Municipal Natural Science Foundation (No.2152020)
文摘Microstructures of Cu-4.7Sn(%) alloys prepared by two-phase zone continuous casting(TZCC)technology contain large columnar grains and small grains.A compound grain structure,composed of a large columnar grain and at least one small grain within it,is observed and called as grain-covered grains(GCGs).Distribution of small grains,their numbers and sizes as well as numbers and sizes of columnar grains were characterized quantitatively by metallographic microscope.Back propagation(BP) artificial neural network was employed to build a model to predict microstructures produced by different processing parameters.Inputs of the model are five processing parameters,which are temperatures of melt,mold and cooling water,speed of TZCC,and cooling distance.Outputs of the model are nine microstructure quantities,which are numbers of small grains within columnar grains,at the boundaries of the columnar grains,or at the surface of the alloy,the maximum and the minimum numbers of small grains within a columnar grain,numbers of columnar grains with or without small grains,and sizes of small grains and columnar grains.The model yields precise prediction,which lays foundation for controlling microstructures of alloys prepared by TZCC.
