The yield strength and ultimate tensile strength of ferritic steel weld metal have been expressed as functions of chemical composition, the heat input during welding, and of the heat treatment given after welding is completed. The method involved a neural network analysis of a vast and quite general database assembled from publications on weld metal properties. The outputs of the model have been assessed in a variety of ways, including specific studies of model predictions for the so-called carbon-manganese and 2.25Cr1Mo systems. Where possible, comparisons have also been made against corresponding methods which use simple physical metallurgical principles. The models created are believed to have been trained on the largest weld metal database to date, and are shown to capture vital metallurgical trends. The computer programs associated with the work have been made freely available on the world-wide-web.
Science and Technology of Welding and Joining, Vol.5, 2000, pp. 135-147.
Download PDF File
Download Tex File
Part II of this paper