Based on the principle of BP neural networks, the rolling force model is established after thoroughly analyzing and reprocessing the data of 1 350 mm aluminium foil mill. It states that the difference between the outp...Based on the principle of BP neural networks, the rolling force model is established after thoroughly analyzing and reprocessing the data of 1 350 mm aluminium foil mill. It states that the difference between the output of artificial neural networks rolling force model and the real value is in the order of 3 percent. The model reflects the real feature of process.展开更多
A systematic study has been conducted aiming to attain an insight into the influence of coefficient of roll speed asymmetry, crystal orientation and structure on the deformation behavior, and crystallographic orientat...A systematic study has been conducted aiming to attain an insight into the influence of coefficient of roll speed asymmetry, crystal orientation and structure on the deformation behavior, and crystallographic orientation development during foil rolling. Simulations were successfully carried out by using crystal plasticity finite element method（CPFEM）,and a novel computational framework is presented for the representation of virtual polycrystalline grain structures. It has been found that asymmetric rolling（ASR） is more efficient in producing plastic deformation since it develops additional shear strain and activity of slip system compared with symmetric rolling（SR）. For ASR, increase in the length of the shear zone, and decrease in the amount of the pressure and roll force would lead to further reduction. The shear strain path in SR and ASR is strictly influenced by the misorientation of neighbor grains, and corresponding {1 1 1} pole figures offer direct evidence of the spread of crystallographic orientation around the normal direction. The activity of slip systems was examined in detail and found that the predicted results are consistent with the surface layer model. The accuracy of the developed CPFEM model is verified by the fact that the simulated results of roll force coincide well with the experimental results.展开更多
文摘Based on the principle of BP neural networks, the rolling force model is established after thoroughly analyzing and reprocessing the data of 1 350 mm aluminium foil mill. It states that the difference between the output of artificial neural networks rolling force model and the real value is in the order of 3 percent. The model reflects the real feature of process.
基金financially supported by the National Natural Science Foundation of China (Nos. 51374069 and U1460107)
文摘A systematic study has been conducted aiming to attain an insight into the influence of coefficient of roll speed asymmetry, crystal orientation and structure on the deformation behavior, and crystallographic orientation development during foil rolling. Simulations were successfully carried out by using crystal plasticity finite element method（CPFEM）,and a novel computational framework is presented for the representation of virtual polycrystalline grain structures. It has been found that asymmetric rolling（ASR） is more efficient in producing plastic deformation since it develops additional shear strain and activity of slip system compared with symmetric rolling（SR）. For ASR, increase in the length of the shear zone, and decrease in the amount of the pressure and roll force would lead to further reduction. The shear strain path in SR and ASR is strictly influenced by the misorientation of neighbor grains, and corresponding {1 1 1} pole figures offer direct evidence of the spread of crystallographic orientation around the normal direction. The activity of slip systems was examined in detail and found that the predicted results are consistent with the surface layer model. The accuracy of the developed CPFEM model is verified by the fact that the simulated results of roll force coincide well with the experimental results.
