Ultrasonic Prediction of r-value in Deep Drawing Steels.

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概要

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• The textures of five types of deep drawing steels were measured and analyzed using the series expansion method. Modul-r and electromagnetic acoustic (EMAT) techniques were employed to determine the elastic anisotropy in terms of the angular variation of Young's modulus and the ultrasonic velocities, respectively. The plastic anisotropy was assessed by measuring r-values as a function of inclination with respect to the rolling direction. The series expansion formalism was employed for predicting the elastic and plastic anisotropies from the initial texture data. Comparison with the experimental measurements of Young's modulus indicates that the so-called elastic energy method can accurately reproduce the elastic anisotropy if the single crystal elastic constants are appropriately chosen within their ranges of uncertainty. The angular variation of r-value in the rolling plane was calculated from the ODF coefficients by means of a relaxed constraint model (pancake version). The best quantitative agreement is obtained when the CRSS ratio for glide on the {112}‹111› and {110}‹111› slip systems is 1.0, 0.95 and 0.90 for the IF2, IF1 and AKDQ grades, respectively. The ODF coefficients of order greater than 4 were evaluated and calculated non-destructively from the anisotropy of the ultrasonic velocities of the lowest order symmetrical Lamb (S0) and shear horizontal (SH0) waves propagating in the rolling plane. The calculated pole figures based on the ODF coefficients obtained in this way are similar to those derived from complete X-ray data. It is shown that the plastic properties of commercial deep drawing steels are predicted more accurately when the 4th and 6th order ODF coefficients are employed than when only the 4th order ones are used.

• The Iron and Steel Institute of Japanの論文

著者

• Sakata Kei

  Technical Research Laboratories Kawasaki Steel Corporation

• Jonas J.

  Department Of Materials Engineering Mcgill University

• Daniel D.

  Department of Metallurgical Engineering, McGill University

• Sakata Kei

  Technical Research Division, Kawasaki Steel Corporation

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