Childs, THC (2019) Revisiting flow stress modelling for simulating chip formation of carbon and low alloy steels. In: Ozturk, E, (ed.) Procedia CIRP. 17th CIRP Conference on Modelling of Machining Operations, 13-14 Jun 2019, Sheffield, United Kingdom. Elsevier , pp. 26-31.
Abstract
In previous papers the present author has successfully predicted chip formation in machining carbon steels with a model that supposes all carbon steels to have the same flow stress thermal softening and a temperature independent strain rate hardening but to be characterized by individual strain hardening behaviours. It has been necessary to suppose thermal softening to be shifted to higher temperatures than observed experimentally. It is now found alternatively that the thermal softening shift is not required if it is supposed that the strain rate hardening increases slightly in proportion to temperature at temperatures greater than 600°C. The new model results are illustrated and compared to experiment for the low alloy steel BS970:708M40. The relation between flow stress and friction modelling is also discussed.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Editors: |
|
Copyright, Publisher and Additional Information: | © 2019, The Authors. This is an open access article under the terms of the Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/ |
Keywords: | Cutting; Chip formation; Friction modelling |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Mar 2019 11:21 |
Last Modified: | 25 Jun 2023 21:46 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.procir.2019.03.222 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144044 |