tailieunhanh - Artificial Neural Networks Industrial and Control Engineering Applications Part 6

Tham khảo tài liệu 'artificial neural networks industrial and control engineering applications part 6', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 164 Artificial Neural Networks - Industrial and Control Engineering Applications instance in a steel with a carbon content of addition of Nb increases tensile strength by 150 MPa. Fig. 7. Carbon concentration effect in combination with a Silicon b Manganese c Niobium. Application of Bayesian Neural Networks to Predict Strength and Grain Size of Hot Strip Low Carbon Steels 165 Figure 8a displays the effect of strip thickness versus manganese content on the final tensile strength. The results indicate a drop in tensile strength when final thickness is increased. This can be attributed to lower cooling rate of thicker strips. Therefore coarsening takes place and the tensile strength decreases Singh et al. 1998 . This figure also illustrates the more influential effects of manganese on thinner strips. Figure 8b reveals the significance of finishing temperature verses the carbon concentration on tensile strength. It shows that by decreasing finishing temperature the final tensile strength increases. Inter-pass recrystallization and grain growth prevention my causes this effect Preloscan et al. 2002 . The influence of temperatures on tensile strength is not significant when compared with that of chemical composition in specified ranges Botlani-Esfahani et al. 2009b . Fig. 8. Interaction of processing feature a Final thickness and manganese concentration b Finishing temperature and carbon concentration. 166 Artificial Neural Networks - Industrial and Control Engineering Applications Grain size model results The result of this analysis indicates the importance of Si Mn and C contents on grain refinement which is significantly greater than the concentration of other elements. The most effective element for grain refinement is recognized to be that of vanadium. However its concentration in these steels is very low. For testing the results of the model are depicted when the concentrations of elements are on their mean values which mentioned in Table 2 and the