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Prediction of Friction Stir Processed AZ31 Magnesium Alloy Micro-Hardness Using Artificial Neural Networks
Abstract:
Friction stir processing (FSP) is a microstructural modification technique. In FSP, the material undergoes intense plastic deformation, yielding a dynamically recrystallized fine grain structure. One of the most important issues that need to be tackled in this field is the lack of predictive tools. That enables the selection of the optimum parameters required to achieve the desired modifications on the mechanical properties of the processed materials. In this study, the effects of different FSP parameters (rotational and translational speeds) on the resulting micro-hardness of friction stir processed AZ31 magnesium sheets are examined. Variations of micro-hardness with longitudinal and through-thickness positions are also investigated. Artificial neural networks (ANNs) are used to model and predict the resulting micro-hardness.
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91-95
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Online since:
October 2014
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