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Modelling Microstructure and Texture Evolution During Warm Rolling of Strip-Cast Non Grain Oriented Electrical Steel with 3.5wt% Si

  • Tristan Bahs,
  • Aditya Vuppala,
  • Max Müller,
  • Jannik Gerlach,
  • David Bailly,
  • Gerhard Hirt

摘要

Non-grain-oriented (NO) electrical steels are soft magnetic materials that are commonly used in electrical drives and machines. The magnetic properties of NO electrical steels are influenced by the alloying components (Si + Al), sheet thickness, grain size, and crystallographic texture. Compared to the conventional production of NO electrical steel sheets, which includes continuous casting, hot and cold rolling as well as final annealing, the strip casting process route represents a promising alternative. In addition to a shortened process chain and the associated energy savings and emission reductions, the process also shows a potentially positive influence on the crystallographic texture of the semi-finished sheet. In this work, microstructure and texture evolution during warm rolling of NO electrical sheet with Fe-3.5Si-2Al alloy produced via strip casting is investigated. The experimental investigations involve texture and microstructure measurements before and after rolling. A multiscale top-down simulation model was developed for texture prediction during rolling. The model consists of an elastic plastic-based FEM simulation of the warm rolling process, from which the history of the deformation gradient at different locations for the sheet in the roll gap is obtained. This variable is then imposed on a representative volume element developed with the experimental measurements. Their evolution is simulated with the DAMASK crystal plasticity tool. Here, based on the experimental flow curves, a physics-based dislocation density material model is calibrated by deactivating and activating the shear band parameters. Simulations are performed and the results of the texture evolution using the two models are compared with the experiments. The dislocation density model, when combined with shear band parameters, is best suited to accurately predict the texture intensities along the important λ-, α- and γ-fibers for this material and the intensities quantitatively match the experimental results.