Enhanced fatigue performance and surface mechanical properties of AISI 304 stainless steel induced by electropulsing-assisted ultrasonic surface rolling process

Hai-bo Wang; Xin-hua Yang; He Li; Guo-lin Song; Guo-yi Tang

doi:10.1557/jmr.2018.307

journal article·2018-11-28

Enhanced fatigue performance and surface mechanical properties of AISI 304 stainless steel induced by electropulsing-assisted ultrasonic surface rolling process

Hai-bo Wang, Xin-hua Yang, He Li, Guo-lin Song, Guo-yi Tang

Journal of Materials Research· Volume 33· Issue 22

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Source abstract

Abstract

The evolution of fatigue performance and surface mechanical properties of AISI 304 stainless steel induced by the electropulsing-assisted ultrasonic surface rolling process (EP-USRP) was systematically investigated by integrating instrumented indentation, scanning electron microscopy with electron backscatter diffraction, and transmission electron microscopy. The results indicate that higher hardness, greater strength, finer ultra-refined grains, and higher residual compressive stress are formed within the strengthened layer compared with the original ultrasonic surface rolling process (USRP). EP-USRP with the optimized experimental parameters can produce a higher average rotating bending fatigue strength for AISI 304 stainless steel than USRP. Anomalously and noteworthily, all fatigue specimens treated by EP-USRP showed an incomplete fracture, revealing a higher reservation of safety in practical engineering applications. The further modified structure strengthening and stress strengthening induced by EP-USRP are likely the primary intrinsic reasons for the observed phenomena. Furthermore, the influence mechanism of EP-USRP was discussed scrupulously.

Source: expertdata · Quality: candidate unverified · Source record ↗

Research context

Metals & alloys

OpenAlex topics: Surface Treatment and Residual Stress · Electromagnetic Effects on Materials · Metal Alloys Wear and Properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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