PSI - Issue 31

Artyom Chirkov et al. / Procedia Structural Integrity 31 (2021) 80–85

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Artyom Chirkov et al. / Structural Integrity Procedia 00 (2019) 000–000

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Fig. 4. Patterns of plastic strain distribution in computational domain in consecutive instants (a)–(f).

(a) (b) Fig. 5. Kinetic diagram obtained by processing the modeling data (a), ratio of the velocity of plastic strain maximum to the loading velocity (b).

Lu¨ders bands collapse approximately in the middle of the sample. We can conclude that the rate of the Lu¨ders bands propagation is non-stationary with an average integral ratio of band’s velocity to loading velocity ≈ 35 (see Fig. 5b). This ratio finds a good agreement with experimental range observed by Zuev and Barannikova (2014). Next, the linear hardening stage is established which is characterized by inhomogeneous distribution of plastic strain. In this stage, approximately twelve maximums of plastic strain are reliably distinguished along with the A-A profile (Fig. 5a). Note, that once the linear work hardening stage is established, the ratio of the plastic strain maximums velocity drops down to unity (see Fig. 5b). It indicates that relative positions of maximums do not change in the course of plastic flow. In this work, we considered the features of plastic flow of low-carbon steel when specific hardening law is as signed – namely, the linear hardening law. Based on the results of numerical modeling we can draw the following conclusions: • The regularities of plastic flow and inhomogeneous distribution of plastic strain depend on the features of microstructure and dependence of the yield stress on the size of individual grains. The microstructure of material must be explicitly included into consideration when modeling the plastic flow of polycrystalline materials. Otherwise, the distribution of plastic strain does not meet available in the literature experimental data. 5. Conclusions