PREDICTION OF THE PLASTIC ANISOTROPY OF LOW-CARBON STEEL SHEET BY MEANS OF TAYLOR-MODELING

In this paper, a study is presented about the prediction of the r-value of several low-carbon low-alloy steel sheets by means of Taylor-modelling. The purpose of this study was not to identify suitable models predicting the r-values for each type of steel separately, but to find one single model that would be able to predict r-values for any kind of low carbon steel sheet as well as possible. It was shown that the instantaneous r-value diminishes during a tensile test. This evolution is coupled to a change in texture, which was measured and simulated by a Taylor-model using both ideal and real textures. The r-values were calculated in two different ways. The first method used was the series expansion method, the second method is one in which the texture evolution during tensile testing is simulated. A quantitative comparison between measured and calculated data was made, taking the errors introduced by tensile testing and texture measurements into account. It will also be shown that for the purpose of quantitative data analysis, the q-value (contraction coefficient) deserves some preference over the commonly used r-value.