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Predictions of toughness and hardness by using chemical composition and tensile properties in microalloyed line pipe steels
, Article Neural Computing and Applications ; 2014 ; Khalaj, G ; Pouraliakbar, H ; Jandaghi, M. R ; Sharif University of Technology
Abstract
Artificial neural networks with multilayer feed forward topology and back propagation algorithm containing two hidden layers are implemented to predict the effect of chemical composition and tensile properties on the both impact toughness and hardness of microalloyed API X70 line pipe steels. The chemical compositions in the forms of "carbon equivalent based on the International Institute of Welding equation (CEIIW)", "carbon equivalent based on the Ito-Bessyo equation (CEPcm)", "the sum of niobium, vanadium and titanium concentrations (VTiNb)", "the sum of niobium and vanadium concentrations (NbV)" and "the sum of chromium, molybdenum, nickel and copper concentrations (CrMoNiCu)", as well...