4th edition, 2017
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The process of rolling is very complicated and the number of parameters which determines the final properties can be very large. It is extremely difficult therefore to develop a physical model for predicting various properties like yield and tensile strengths. In the present work, a neural network technique which can recognise complex relationships was employed to develop a quantitative method for estimating the yeild and tensile strengths as a function of steel composition and rolling parameters. The model was tested extensively to confirm that the predictions are reasonable in the context of metallurgical principles and other data published in the literature.
Ironmaking and Steelmaking, Vol. 25, 1998, 355-365.
Review of Neural Networks in Materials Science
4th edition, 2017 |
Free download |
Free download |
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