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An artificial neural-network model for impact properties in X70 pipeline steels
Authors:Tohid Azimzadegan  Mahdi Khoeini  Moslem Etaat  Alireza Khoshakhlagh
Affiliation:1. Department of Materials Science and Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran
2. Safa Rolling and Pipe mills Co., Saveh, Iran
Abstract: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 °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.
Keywords:
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