J. T. Niu
,
H. T. Li
,
X. D. Meng and P. Karjaleinen 1) Analysis and Measurement Center
,
Harbin Institute of Technology
,
Harbin 150001
,
China 2) Department of Mechanocal Engineering
,
The University of Oulu
,
Finland
金属学报(英文版)
With the development of modern science and technology, especially computer science, the numerical simulation method has been widely used in material hot-working. Mary achievements have been made in this field by using the numerical simulation method. The numerical simulation method, especially finite element method fully described in this paper.Applications of the numerical simulation method in material hot-working are also discussed. Finally, the future of the numerical simulation method is outlined.
关键词:
numerical simulation
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null
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J. T.Niu
,
L.J.Sun and P.Karjalainen 1) Harbin Institute of Technology
,
Harbin 150001
,
China 2) University of Oulu
,
FIN-90571
,
Oulu
,
Finland
金属学报(英文版)
For the great significance of the prediction of control parameters selected for hot-rolling and the evaluation of hot-rolling quality for the analysis of prod uction problems and production management, the selection of hot-rolling control parameters was studied for microalloy steel by following the neural network principle. An experimental scheme was first worked out for acquisition of sample data, in which a gleeble-1500 thermal simolator was used to obtain rolling temperature, strain, stain rate, and stress-strain curves. And consequently the aust enite grain sizes was obtained through microscopic observation. The experimental data was then processed through regression. By using the training network of BP algorithm, the mapping relationship between the hotrooling control parameters (rolling temperature, stain, and strain rate) and the microstructural paramete rs (austenite grain in size and flow stress) of microalloy steel was function appro ached for the establishment of a neural network-based model of the austeuite grain size and flow stress of microalloy steel. From the results of estimation made with the neural network based model, the hot-rolling control parameters can be effectively predicted.
关键词:
microalloy steel
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null
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null
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null
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null
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