An artificial neural network model for predicting mechanical properties of C Mn (V-Nb-Ti) pipeline steel in industrial production conditions

A. Guedri; S.Tlili; B. Merzoug; A. Zeghloul

Center of Academic Publications

An artificial neural network model for predicting mechanical properties of C Mn (V-Nb-Ti) pipeline steel in industrial production conditions

https://www.univ-soukahras.dz/en/publication/article/84

A. Guedri, S.Tlili, B. Merzoug and A. Zeghloul (2007) An artificial neural network model for predicting mechanical properties of C Mn (V-Nb-Ti) pipeline steel in industrial production conditions. International Review of Mechanical Engineering (I.RE.M.E.), ISSN: 1970– 8734, November 2007 , 6(1), 666-674, Praise worthy prize

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The mechanical properties of API X60/X70 microalloyed steel were investigated with industrial thermomechanical experiments. The many parameters of processes obtained during production of the plant were systematically changed to optimise the strength and toughness properties. The optimised parameters were used for the production of the API X60/X70 steel. However, it is not easy to determine as to what parameters under which conditions influence the mechanical properties of the material. Therefore, in this study, a generalised regression neural network was developed to predict the mechanical properties as a function of experimental conditions. The predicted values of the yield and tensile strengths using the neural network are found to be in good agreement with the actual values from the experiments.

Item Type:	Journal
Divisions:	» Laboratory of Management, Maintenance and Rehabilitation Of Facilities and Urban Infrastructure
ePrint ID:	84
Date Deposited:	2014-10-30
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/84