Science and Technology of Welding & Joining · 2000 · 42 citations · 6 references
EngineeringMaterials EngineeringMaterials ScienceMachine LearningMechanical Behavior Of MaterialsMetallurgyAlloysMetalsPhysical MetallurgySteel MaterialsWeldingWelding ProcessesFerritic SteelsMetallurgical CharacterizationNeural Network ModelingNeural Network PredictionSteel WeldingTensile StrengthUltimate Tensile StrengthYield Strength
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 the heat treatment given after welding is completed. The method involved a neural network analysis of a vast and fairly 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 C–Mn and 2.25Cr–1Mo systems. Where possible, comparisons have also been made with 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.
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A Practical Bayesian Framework for Backpropagation Networks
David Mackay · Neural Computation · 1992 · 2.9K citations