L. S. Goruleva, S. M. Zadvorkin, D. I. Vichuzhanin, R. A. Savrai, P. A. Skorynina
AN EXPERIMENTAL AND COMPUTATIONAL STUDY OF THROUGH-DEPTH STRAIN DISTRIBUTION DURING FRICTIONAL TREATMENT OF A METASTABLE AUSTENITIC STEEL
DOI: 10.17804/2410-9908.2023.6.132-144 Frictional treatment, as a method of surface plastic deformation, forms a gradient hardened layer. In the case of metastable steels, this hardening is due, among other things, to the formation of strain-induced α'-martensite. The most reliable information about the thickness of this hardened layer can be obtained by measuring the hardness on transverse sections. This paper compares strain distribution through the depth of the hardened layer, obtained from layer-by-layer phase analysis and finite element modeling, with the data of durametric studies for the AISI 321 metastable steel subjected to frictional treatment under various loads on the indenter. A satisfactory coincidence of the distributions of the α'-phase concentration and hardness through the depth is observed only for the specimen subjected to frictional treatment at a maximum load of 400 N on the indenter. At the other loads on the indenter, the thickness of the layer containing α'-martensite is lower than the thickness of the hardened layer estimated from the durametric studies. In contrast, it is shown that, for all the loads applied to the indenter during frictional treatment, the through-depth distributions of the calculated values of equivalent plastic strain obtained from finite element modeling agree satisfactorily with the experimental hardness values.
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Article reference
An Experimental and Computational Study of Through-Depth Strain Distribution During Frictional Treatment of a Metastable Austenitic Steel / L. S. Goruleva, S. M. Zadvorkin, D. I. Vichuzhanin, R. A. Savrai, P. A. Skorynina // Diagnostics, Resource and Mechanics of materials and structures. -
2023. - Iss. 6. - P. 132-144. - DOI: 10.17804/2410-9908.2023.6.132-144. -
URL: http://eng.dream-journal.org/issues/2023-6/2023-6_425.html (accessed: 11/21/2024).
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