PSI - Issue 40

V.S. Kanakin et al. / Procedia Structural Integrity 40 (2022) 194–200

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Kanakin V.S. et al. / Structural Integrity Procedia 00 (2019) 000 – 000

Fig. 5. The strain and strain rate dependences of flow stress for the AlMg6/10% SiC MMC at 350  С (a) and 450  С (b): experimental (black curve) and predicted by the neural network (red curve). 4. Conclusions 1. The obtained experimental flow stress curves of the AlMg6/10% SiC metal matrix composite at temperatures ranging from 300 to 500 °С and strain rates ranging from 0.1 to 5 s − 1 indicate dynamic recrystallization, which causes the appearance of peaks on the flow stress curves in the entire temperature – rate range under study. 2. It has been shown that the constructed neural network can predict the rheological behavior of the AlMg6/10% SiC metal matrix composite at temperatures ranging from 300 to 500 °С and strain rates of 0.1 to 5 s − 1 with acceptable engineering accuracy. Acknowledgments The work was partially financially supported by RFBR (project 19-08-00765) in the part of modeling the rheological behavior of metal matrix composites; it was performed within the research conducted by the Institute of Engineering Science, Ural Branch of the Russian Academy of Sciences (project No. AAAA-A18-118020790140-5) in the part of studying the rheological behavior of materials. References Chawla, N. and Chawla, K.K.., 2013., Metal Matrix Composites., New York, NY: Springer New York. https://doi.org/10.1007/978-1-4614-9548 2. Gourdet, S, and Montheillet, F., 2000. An Experimental Study of the Recrystallization Mechanism during Hot Deformation of Aluminium, Materials Science and Engineering: A 283(1 – 2), 274 – 288. http://dx.doi.org/10.1016/S0921-5093(00)00733-4. Jiang, D., Liu, R., Wang, C., Wang, Z., Imai, T., 1999. Microstructure and Superplasticity of an Al-Zn-Mg-Cu Alloy. Journal of Materials Science 34(14), 3363 – 3366. https://doi.org/10.1023/A:1004629031261. Kondratev, N.S., Trusov, P.V., 2016. Calculation of the Intergranular Energy in Two-Level Physical Models for Describing Thermomechanical Processing of Polycrystals with Account for Discontinuous Dynamic Recrystallization. International Journal of Nanomechanics Science and Technology 7(2), 107 – 122. https://doi.org/10.1615/NanomechanicsSciTechnolIntJ.v7.i2.20. Konovalov, A.V., Smirnov, A.S., 2008. Viscoplastic Model for the Strain Resistance of 08Kh18N10T Steel at a Hot-Deformation Temperature. Russian Metallurgy (Metally) 2008(2), 138 – 141. https://doi.org/10.1134/S0036029508020092. Lin, Y.C., Zhang, J., Zhong, J., 2008. Application of Neural Networks to Predict the Elevated Temperature Flow Behavior of a Low Alloy Steel. Computational Materials Science 43(4), 752 – 758. https://doi.org/10.1016/j.commatsci.2008.01.039.