Skip to main content

Research Repository

Advanced Search

A numerical methodology for predicting tool wear in Friction Stir Welding

Hasan, Ahmed; Bennett, Chris; Shipway, P.H.; Cater, S.; Martin, J.

Authors

Ahmed Hasan

CHRIS BENNETT C.Bennett@nottingham.ac.uk
Professor of Solid Mechanics

S. Cater

J. Martin



Abstract

A novel methodology for predicting tool wear in FSW based on a CFD model, coupled with a modified Archard equation, is presented considering the effect of the deformation of the highly viscous flow around the tool on tool wear. A validation process is proposed to ensure robust results when using this methodology. A study was carried out to predict the wear on a dome shaped FSW tool, indicating that high wear was predicted at the shoulder edge due to rapidly changing flow, and that the interaction of the axial flow with the pin causes a bifurcation of the flow and an associated increase in pressure at the mid axial position of the pin, again leading to high wear in this location. The proposed approach could be used as a method for calculating tool wear and determining the effective limits of tool use, without the need for experimental trials.

Citation

Hasan, A., Bennett, C., Shipway, P., Cater, S., & Martin, J. (2017). A numerical methodology for predicting tool wear in Friction Stir Welding. Journal of Materials Processing Technology, 241, https://doi.org/10.1016/j.jmatprotec.2016.11.009

Journal Article Type Article
Acceptance Date Nov 9, 2016
Online Publication Date Nov 11, 2016
Publication Date Mar 31, 2017
Deposit Date Nov 17, 2016
Publicly Available Date Nov 12, 2018
Journal Journal of Materials Processing Technology
Print ISSN 0924-0136
Electronic ISSN 0924-0136
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 241
DOI https://doi.org/10.1016/j.jmatprotec.2016.11.009
Keywords Friction stir welding; Computational fluid dynamics; Tool wear; Modelling
Public URL https://nottingham-repository.worktribe.com/output/853126
Publisher URL http://www.sciencedirect.com/science/article/pii/S0924013616303909

Files





You might also like



Downloadable Citations