1. CONSTITUTIVE MODEL OF 3Cr23Ni8Mn3N HEAT-RESISTANT STEEL BASED ON BACK PROPAGATION (BP) NEURAL NETWORK(NN).
- Author
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CAI, Z. M., JI, H. C., PEI, W. C., HUANG, X. M., LI, W. D., and LI, Y. M.
- Subjects
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BACK propagation , *ARTIFICIAL neural networks , *HEAT resistant materials , *STRESS-strain curves , *STRAIN rate , *STEEL - Abstract
The 3Cr23Ni8Mn3N heat-resistant steel was subjected to isothermal constant strain rate compression experiments using a Gleeble - 1 500D thermal simulator. The thermal deformation behavior in the range of deformation temperature 1 000 - 1 180 °C and strain rate 0,01 - 10 s-1 was studied. Based on experimental data, the stress-strain curves of 3Cr23Ni8Mn3N were established. And the constitutive relation of BP neural network (3 × 10 × 10 × 1) was constructed. The flow stress was predicted and compared by the ANN constitutive model. The correlation coefficient (R) is 0,999, and the average relative error (AARE) is 0,697%. The results show that the ANN constitutive model has high accuracy for predicting the thermal deformation behavior of 3Cr23Ni8Mn3N. The model can provide a good reference value for thermal processing. [ABSTRACT FROM AUTHOR]
- Published
- 2019