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Model parameter identification of the Hansel-Spitttel flow stress equation by statistical regression
Kyunghoon Lee(이경훈),Woojin Song(송우진) 대한기계학회 2015 대한기계학회 춘추학술대회 Vol.2015 No.11
For forming simulation flow stress modeling is imperative in emulating the mechanical behavior of a material of interest. Flow stress models are typically determined by model parameter identification via least squares methods. Instead, this research tackles the same problem of model parameters identification by statistical regression. To determine the parameters of a flow stress model, this research presumes an additive noise model for experimental strain and stress measurements in a log space. Based on a probabilistic formulation, this research draws on the method of maximum likelihood to derive the parameters of a flow stress model. For illustration, we used the Hansel-Spittel flow stress equation with strain and stress measurements of AA1070 aluminum alloys. We found that the fitted Hansel-Spittel flow stress model agrees well with the strain and stress measurements.