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Physics of Metals
ArticleName Optimization of modes of pendular surface plastic deformation for intensification of the stress-strain state of carbon steel parts
DOI 10.17580/chm.2023.01.09
ArticleAuthor S. A. Zaides, Kho Min Kuan

Irkutsk National Research Technical University, Irkutsk, Russia:

S. A. Zaides, Dr. Eng., Prof., Dept. of Materials Science, Welding and Additive Technologies, e-mail:
Kho Min Kuan, Postgraduate Student, Dept. of Materials Science, Welding and Additive Technologies, e-mail:


The results of modeling on the influence of the main parameters and modes of the pendulum SPD process on the stress-strain state (SSS) of the surface layer are presented. It has been established that the obtained dependences of the SSS indicators on the technological parameters of the pendulum RPM process are not linear, for the solution of which polynomial equations are used as input data in the Statictiska 10.1 software package. Using the software package Statictiska 10.1, the optimal modes of the pendulum RPM process were determined. It has been established that the optimal modes of the pendulum SPD, which allow simultaneously obtaining the maximum intensity values of temporary (560–580 MPa) and residual compressive stresses (340–350 MPa) of the surface layer of hardened parts, are quite close. To optimize the value of work hardening (h), a significant increase in the value of the radial interference and a decrease in the value of the longitudinal feed are required, which lead to the approach of the intensity of temporary stresses to the u l timate strength of the material (600 MPa), and the intensity of residual stresses to the yield strength of the material (360 MPa). Such regimes lead to a decrease, and perhaps even to a complete removal of the residual stresses of the hardened layer, as well as to a decrease in the degree of work hardening. Thus, the rational maximum value of the hardened layer with pendulum RPM is 2.45 mm.

keywords Surface plastic deformation, temporary and residual stresses, plastic deformation, statistical processing

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