Prediction of strain distribution during the plane strain tensile test based on artificial neural networks
DOI:
https://doi.org/10.32972/dms.2023.006Kulcsszavak:
FEM, ANN, RSM, Tensile test, Plan strainAbsztrakt
In this study, finite element method was used to study the effects of various notch geometries on the strain field distributions during the plane strain tensile test for cold-rolled steel (DC01). The artificial neural network approach (ANN) and the response surface meth-odology (RSM) were adopted to develop the mathematical prediction models applied in the optimization procedure. The strain state was expressed by self-defined metrics, namely, the Plane Strain State Index (PSSI) and the Homogeneity Index (HI) were predicted by changing the notch angle (X degree), notch width (d mm), and notch length (c mm). The Quadratic mathematical models obtained by the RSM, and ANN presented the evolution of PSSI, and HI based on (X, d, and c). The results show that the ANN method provides more precise results compared to those of the RSM approach.
Hivatkozások
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