Modeling and Numeric Analysis of the Microstructure of the hot rolling Plate Using Artificial Neural Network
In the present paper, an artificial neural network model for predicting transformed microstructure under conventional rolling and thermo-mechanical controlled processing (TMCP) was proposed. The model uses austenite grain size and retained strain, which can be calculated by using microstructure evolution models, together with measured cooling rate and chemical compositions as inputs and the outputs are ferrite grain size and ferrite fraction. The prediction results show that the model can predict the transformed microstructure with good agreements with measured ones, and is better than empirical equations. Also the effect of alloying elements on transformed products was analyzed by using the model,the tendency is the same with the reported papers. The model can be used further to the optimization of processing parameters-microstructure-properties in TMCP.
artificial neural network TMCP microstructure ferrite grain size
TAN Wen LIU Zhen-Yu MA Li-Qiang XUE Wen-Ying WU Di WANG Guo-Dong
The State Key Laboratory of Rolling and Automation P. O. Box, No.105, Northeastern University, Shenyang, 110004, P. R. China
国际会议
辽宁
英文
2006-10-21（万方平台首次上网日期，不代表论文的发表时间）