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Abstract: The effect of processing parameters on its microstructure
after solution treatment is studied by isothermal compression test and
metallurgical analysis, The predicting model for the relation between
equivalent grain size and recrystallized grain volume fraction with
strain, strain rate and temperature for Ti-15-3 alloy is developed with
an artificial neural network method, This model is incorporated into
rigid-viscoplastic thermo-coupled FEM Code and the microstructure of
Ti-15-3 alloy after hot back-extrusion process and solution treatment is
simulated.
Corresponding experimental research is performed. The simulated results
are in good with the measured ones. These studies are significant for
determining the processing parameters of Ti-15-3 alloy.
Key words: Ti-15-3 alloy Microstructure Artificial neural network
FEM
CLC No: TG302
Received
20010510, received in revised form 20020104
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