Javaheri, V., Pohjonen, A., Asperheim, J. I., Ivanov, D., & Porter, D. (2019). Physically based modeling, characterization and design of an induction hardening process for a new slurry pipeline steel. Materials & Design, 182, 108047. https://doi.org/10.1016/j.matdes.2019.108047
Physically based modeling, characterization and design of an induction hardening process for a new slurry pipeline steel
|Author:||Javaheri, Vahid1; Pohjonen, Aarne1; Asperheim, John Inge2;|
1Materials and Mechanical Engineering, Centre for Advanced Steels Research, University of Oulu, 90014 Oulun yliopisto, Finland
2R&D, EFD Induction a.s., Skien, Norway
|Online Access:||PDF Full Text (PDF, 9.2 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019080823686
|Publish Date:|| 2019-08-08
Numerical and Gleeble experimental data are combined to predict potential microstructure and hardness profiles through the wall thickness of an induction hardened slurry transportation pipe made of a recently developed 0.4 wt% C, Nb-microalloyed steel. The calculated thermal history of various positions through the wall thickness of an industrial pipe (400 mm diameter, 10 mm thick) were combined with a model that predicts the phase transformations, microstructures and final hardness values on heating and cooling along arbitrary thermal cycles. The accuracy of the hardness profile predictions was verified by experimental data, i.e. reproducing the thermal cycles on a Gleeble thermomechanical simulator. The results indicated that the approach should be a feasible way to optimize induction heating and cooling parameters to obtain desired hardness profiles through the wall thickness.
Materials & design
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
216 Materials engineering
The authors are grateful for financial support from the European Commission under grant number 675715 – MIMESIS – H2020-MSCA-ITN-2015, which is a part of the Marie Sklodowska-Curie Innovative Training Networks European Industrial Doctorate programme.
|EU Grant Number:||
(675715) MIMESIS - Mathematics and Materials Science for Steel Production and Manufacturing
© 2019 The Author(s). Published by Elsevier Ltd.This is an open access article under the CCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).