An Artificial Neural Network Model for Predicting Mechanical Properties of CMn (V-Nb-Ti) Pipeline Steel in Industrial Production Conditions


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Abstract


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.
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Keywords


Microalloyed Steel; Mechanical Properties; Artificial Neural Network; Regression Neural Network

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