Loading…
The role of vibration and pass number on microstructure and mechanical properties of AZ91/SiC composite layer during friction stir processing
In this study, nano-sized SiC particles are added to AZ91 magnesium alloy using friction stir processing (FSP) and friction stir vibration processing (FSVP) to produce surface nano-composite layers. FSVP is a modified method of FSP in which the specimen is vibrated during FSP. The influence of FSP a...
Saved in:
Published in: | Proceedings of the Institution of Mechanical Engineers. Part C, Journal of mechanical engineering science Journal of mechanical engineering science, 2022-03, Vol.236 (5), p.2312-2326 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | In this study, nano-sized SiC particles are added to AZ91 magnesium alloy using friction stir processing (FSP) and friction stir vibration processing (FSVP) to produce surface nano-composite layers. FSVP is a modified method of FSP in which the specimen is vibrated during FSP. The influence of FSP and FSVP pass numbers on mechanical and microstructural behaviors of the developed surfaces is investigated. It is indicated that nano-composite layers produced by FSVP have finer microstructures compared to those produced by FSP, and nano-sized particles are distributed more homogeneously. Furthermore, mechanical properties including hardness, scratch resistance, ductility, and strength of FSV processed specimens, were higher than those related to FS processed specimens. The results show a decline in the porosity content as the FSP passes are increased. Also, the compressive strength of the FSVP-ed composites is higher than those for the FSP-ed samples. It is also noticed that an increase in the vibration frequency during the FSVP process causes a more uniform dispersion of composite particles and thus, decreases particle clustering. |
---|---|
ISSN: | 0954-4062 2041-2983 |
DOI: | 10.1177/09544062211024281 |