A comprehensive mathematical model was established and used to simulate the macro and microstructure evolution during the production process of 5CrNiMo steel ingot by electroslag remelting （ESR） method. Along the in...A comprehensive mathematical model was established and used to simulate the macro and microstructure evolution during the production process of 5CrNiMo steel ingot by electroslag remelting （ESR） method. Along the ingot height, the macrostructure distribution characteristics changed from vertical, fine columnar grains to tilted, coarse columnar grains, and this transformation process occurred at the very beginning of ESR. In the cross section of the ingot, there were three grain morphology regions and two grain type transition regions from the outside to the center of the ingot. These regions were the fine columnar grain region, columnar competitive growth transition re gion, coarse columnar grain region, columnar to equiaxed grain transition （CET） region, and coarse equiaxed grain region. The influence of the remelting rate on the macrostructure and mlcrostructure was investigated using a series of experiments and simulations. The results showed that a low remelting rate could produce a small grain growth angle （GGA） ; the average secondary dendrite arm spacing （SDAS） firstly decreased and then increased as the remelting rate increased. An excessively high or low remelting rate can increase the GGA and average SDAS in ingots. Thus, the remelting rate should be controlled within a suitable range to reduce composition microsegregation and microshrinkage in the ingot to produce an ESR ingot with satisfactory hot forging performance.展开更多
The continuous casting technological parameters have a great influence on the secondary dendrite arm spacing of the slab, which determines the segregation behavior of materials. Therefore, the identification of techno...The continuous casting technological parameters have a great influence on the secondary dendrite arm spacing of the slab, which determines the segregation behavior of materials. Therefore, the identification of technological parameters of continuous casting process directly impacts the property of slab. The relationships between continuous casting technological parameters and cooling rate of slab for spring steel were built using BP neural network model, based on which, the relevant secondary dendrite arm spacing was calculated. The simulation calculation was also carried out using the industrial data. The simulation results show that compared with that of the traditional method, the absolute error of calculation result obtained with BP neural network model reduced from 0. 015 to 0. 0005, and the relative error reduced from 6, 76 % to 0.22 %. BP neural network model had a more precise accuracy in the optimization of continuous casting technological parameters.展开更多
基金Item Sponsored by National Natural Science Foundation of China(51165030)
文摘A comprehensive mathematical model was established and used to simulate the macro and microstructure evolution during the production process of 5CrNiMo steel ingot by electroslag remelting （ESR） method. Along the ingot height, the macrostructure distribution characteristics changed from vertical, fine columnar grains to tilted, coarse columnar grains, and this transformation process occurred at the very beginning of ESR. In the cross section of the ingot, there were three grain morphology regions and two grain type transition regions from the outside to the center of the ingot. These regions were the fine columnar grain region, columnar competitive growth transition re gion, coarse columnar grain region, columnar to equiaxed grain transition （CET） region, and coarse equiaxed grain region. The influence of the remelting rate on the macrostructure and mlcrostructure was investigated using a series of experiments and simulations. The results showed that a low remelting rate could produce a small grain growth angle （GGA） ; the average secondary dendrite arm spacing （SDAS） firstly decreased and then increased as the remelting rate increased. An excessively high or low remelting rate can increase the GGA and average SDAS in ingots. Thus, the remelting rate should be controlled within a suitable range to reduce composition microsegregation and microshrinkage in the ingot to produce an ESR ingot with satisfactory hot forging performance.
文摘The continuous casting technological parameters have a great influence on the secondary dendrite arm spacing of the slab, which determines the segregation behavior of materials. Therefore, the identification of technological parameters of continuous casting process directly impacts the property of slab. The relationships between continuous casting technological parameters and cooling rate of slab for spring steel were built using BP neural network model, based on which, the relevant secondary dendrite arm spacing was calculated. The simulation calculation was also carried out using the industrial data. The simulation results show that compared with that of the traditional method, the absolute error of calculation result obtained with BP neural network model reduced from 0. 015 to 0. 0005, and the relative error reduced from 6, 76 % to 0.22 %. BP neural network model had a more precise accuracy in the optimization of continuous casting technological parameters.
