3D Non-destructive Characterisation of Texture Evolution in Electrical Steels with Laboratory Diffraction Contrast Tomography

The core loss and magnetic induction of electrical steels are dependent on the microstructure and texture of the material, which are produced by the thermo-mechanical processing. After a conventional rolling process, crystal orientations of the α-(//RD) and γ-(//ND) fibers are strongly present in the final texture. These fibers have a drastically negative effect on the magnetic properties of electrical steels. By applying asymmetric rolling, significant shear strains could be introduced across the thickness of the sheet and thus a deformation texture with more magnetically favorable components is expected. In this study, an electrical steel of 1.23 wt.% Si was subjected to asymmetric warm rolling in a rolling mill with different roll diameters. The evolutions of both deformed and annealed textures were investigated. The texture evolution during asymmetric warm rolling was analyzed by crystal plasticity simulations using the ALAMEL model. A good fit between measured and calculated textures was obtained. The annealing texture could be understood in terms of an oriented nucleation model that selects crystal orientations with a lower than average stored energy of plastic deformation.

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Texture Evolution during the Processing of Electrical Steels with 0.5% Si and 1.25% Si

ISIJ International ◽

10.2355/isijinternational.44.1733 ◽

2004 ◽

Vol 44 (10) ◽

pp. 1733-1737 ◽

Cited By ~ 15

Author(s):

Marcos F. de Campos ◽

Fernando J. G. Landgraf ◽

Ivan G. S. Falleiros ◽

Gabriela C. Fronzaglia ◽

Henrique Kahn

Keyword(s):

Texture Evolution ◽

Electrical Steels

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Identification of magnetic induced strain of electrical steels using non-destructive acceleration measurement and inverse vibration modeling

Journal of Sound and Vibration ◽

10.1016/j.jsv.2020.115806 ◽

2021 ◽

Vol 492 ◽

pp. 115806

Author(s):

E. Salloum ◽

O. Maloberti ◽

S. Panier ◽

M. Nesser ◽

P. Klimczyk ◽

...

Keyword(s):

Acceleration Measurement ◽

Electrical Steels ◽

Inverse Vibration ◽

Non Destructive ◽

Vibration Modeling

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Texture Optimization in Non-Oriented Electrical Steels: The Role of the Goss Texture Component

Materials Science Forum ◽

10.4028/www.scientific.net/msf.495-497.543 ◽

2005 ◽

Vol 495-497 ◽

pp. 543-554 ◽

Cited By ~ 4

Author(s):

Fernando José Gomes Landgraf ◽

Sebastião Da Costa Paolinelli ◽

Marco Antônio Da Cunha ◽

Marcos Flavio de Campos

Keyword(s):

Magnetic Properties ◽

Magnetic Property ◽

Texture Component ◽

Texture Evolution ◽

Goss Texture ◽

Electrical Steels

The non-oriented electrical steels, produced with different processing procedures, base their magnetic property improvement mainly on the increase of the Goss component. This paper relates the anisotropy of magnetic properties to texture, describes the texture evolution in both the Fully-processed and the Semi-processed classes of electrical steels.

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Microstructure and Texture Evolution in Non-oriented Electrical Steels Along Novel Strip Casting Route and Conventional Route

steel research international ◽

10.1002/srin.201500145 ◽

2015 ◽

Vol 87 (5) ◽

pp. 589-598 ◽

Cited By ~ 4

Author(s):

Hai-Tao Liu ◽

J. Schneider ◽

A. Stöcker ◽

A. Franke ◽

Fei Gao ◽

...

Keyword(s):

Texture Evolution ◽

Strip Casting ◽

Electrical Steels

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Texture Evolution during Recrystallization in Nonoriented Electrical Steels

Materials Science Forum ◽

10.4028/www.scientific.net/msf.550.533 ◽

2007 ◽

Vol 550 ◽

pp. 533-538 ◽

Cited By ~ 1

Author(s):

Jong Tae Park ◽

Jae Young Choi ◽

Jae Kwan Kim ◽

Jerzy A. Szpunar

Keyword(s):

Magnetic Properties ◽

Late Stage ◽

Recrystallization Texture ◽

Early Stage ◽

Texture Evolution ◽

Area Fraction ◽

Electrical Steels ◽

New Information

In nonoriented electrical steels, the control of texture has received little attention, and hence there is an unexplored possibility to improve the magnetic properties of nonoriented steels through texture control. Furthermore, the formation of recrystallization texture in these steels has not yet been systematically studied. In this study, such systematic investigations are undertaken for nonoriented electrical steels with 2% Si. New information obtained from EBSD measurements on partially recrystallized specimens will allow us to know what is happening during the recrystallization stage. The formation of recrystallization texture is much better explained by oriented nucleation. This is supported by the fact that the area fraction of nuclei or recrystallized grains with specific orientations for all new grains remains almost constant during the progress of recrystallization. Most nuclei have a high misorientation relationship with the surrounding deformed matrix: 25~55. The main texture components of nuclei or recrystallized grains during the progress of recrystallization are Goss and {111}<112>. Deformed {111}<110> and {111}<112> grains generally disappear at the early stage of recrystallization whereas deformed {001}<110> and {112}<110> grains are mostly consumed at the late stage of recrystallization.

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A flexible and standalone forward simulation model for laboratory X-ray diffraction contrast tomography

Acta Crystallographica Section A Foundations and Advances ◽

10.1107/s2053273320010852 ◽

2020 ◽

Vol 76 (6) ◽

pp. 652-663 ◽

Cited By ~ 1

Author(s):

H. Fang ◽

D. Juul Jensen ◽

Y. Zhang

Keyword(s):

Crystal Structure ◽

Simulation Model ◽

Forward Simulation ◽

X Ray Diffraction ◽

Bulk Materials ◽

X Ray ◽

Diffraction Contrast ◽

Input Structure ◽

Grain Orientations ◽

Non Destructive

Laboratory X-ray diffraction contrast tomography (LabDCT) has recently been developed as a powerful technique for non-destructive mapping of grain microstructures in bulk materials. As the grain reconstruction relies on segmentation of diffraction spots, it is essential to understand the physics of the diffraction process and resolve all the spot features in detail. To this aim, a flexible and standalone forward simulation model has been developed to compute the diffraction projections from polycrystalline samples with any crystal structure. The accuracy of the forward simulation model is demonstrated by good agreements in grain orientations, boundary positions and shapes between a virtual input structure and that reconstructed based on the forward simulated diffraction projections of the input structure. Further experimental verification is made by comparisons of diffraction spots between simulations and experiments for a partially recrystallized Al sample, where a satisfactory agreement is found for the spot positions, sizes and intensities. Finally, applications of this model to analyze specific spot features are presented.

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