Tension leveling is an important process in the steel industry for producing steel strips with high quality. To achieve the finite element (FE) analysis of tension leveling with high accuracy, a constitutive model for 3D stress and strain conditions, which can describe the material behavior in tension leveling (e.g., anisotropy, Bauschinger effect, etc.), is constructed in this investigation by using the Hill48 anisotropic yield criterion with the nonassociated flow rule and mixed hardening. The constructed constitutive model is implemented in ABAQUS using a user-defined material (UMAT) subroutine with an implicit integrated algorithm. In the FE analysis, a 3D analytical rigid body and eight-node solid elements are used for the leveler roll and strip, respectively. The accuracy of the FE analysis results is validated by comparison with experimental and simulation results from Yoshida and Urabe's research on SPCC strips. Tension leveling simulations to correct flatness defects are also conducted for SPFC980 strips. The analysis results show the leveling effect of tension leveling for high strength steel strips.
Cold rolling is widely employed in the manufacturing industry for the production of metal plates. In the cold rolling process, the thickness reduction of the metal plate under the recrystallization temperature generates severe anisotropy; this influences the subsequent forming processes. Therefore, the generation and prediction of metal plate anisotropy during cold rolling is a highly interesting research topic involving upstream studies of sheet metal forming. In this study, using the finite element method with zooming analysis, we established an efficient elastic–plastic analysis method to predict the metal plate texture after cold rolling. This method for cold rolling texture prediction was confirmed by comparing the experimental and simulation results of cold rolling for an S45C plate with a body-centered cubic lattice. Further, the numerical analysis method proposed in this study can contribute to the study of anisotropy as an alternative to experimental approaches.
A new hot rolling & Run Out Table cooling simulator is constructed. The simulator permits continuous collation of process data including in-situ temperature measurement at numerous positions of the strip steel. Tensile properties and microstructural analysis of the hot rolled strip are correlated to the collated process data. A numerical model including phase transformation and latent heat evolution is constructed and calibrated against the experimental data. The resulting numerical model can be used to efficiently predict the optimal process parameters for manufacturing hot rolled strip steels, while the new hot rolling & Run Out Table cooling simulator can be used to efficiently validate the numerical simulation results before up-scaling to the industrial hot mill.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.