An artificial neural-network model for impact properties in X70 pipeline steels

作者：Azimzadegan Tohid; Khoeini Mahdi; Etaat Moslem^*; Khoshakhlagh Alireza

来源：Neural Computing & Applications, 2013, 23(5): 1473-1480.

DOI：10.1007/s00521-012-1097-9

• Artificial neural network
• Pipeline steels
• Mechanical properties
• Impact test

An artificial neural-network (ANN) model has been developed for the analysis and simulation of the correlation between the mechanical properties and composition and thermomechanical treatment parameters of high strength, low alloy steels. The input parameters of the model consist of alloy compositions (C, Si, Mn, P, S, Cu, Ni, Cr, Mo, Ti, V, Nb, Ca, Al, B) and tensile test results (yield strength, ultimate tensile strength, percentage elongation). The outputs of the ANN model include impact energy (-10 A degrees C). The model can be used to calculate the properties of low alloy steels as a function of alloy composition and thermomechanical treatment variables. The current study achieved a good performance of the ANN model, and the results are in agreement with experimental knowledge.

• 出版日期2013-10