Approach for modelling the Taylor-Quinney coefficient of high strength steels

verfasst von
Bernd Arno Behrens, Alexander Chugreev, Florian Bohne, Ralf Lorenz
Abstract

Precise knowledge of the temperature that arises in the material during plastic forming is of crucial importance, as it has a significant influence on material behaviour and therefore on the forming process. In order to describe the amount of heat that is generated during plastic forming accurately, the Taylor-Quinney coefficient β was introduced as the ratio of dissipated heat to plastic work and generally assumed to be a constant value. However, recent studies have shown that there is a dependency on material and process-specific parameters. In this study, the Taylor-Quinney coefficient β is shown as a function of strain and being influenced by the test specific strain rate and stress state. The tested material is a dual-phase steel HCT980X. The uniaxial tensile test and the Marciniak test with different tallied specimen at forming-relevant global strain rates were investigated. By means of thermographic and optical measuring systems the temperature and local strains were recorded during the tests. Based on an approach similar to the finite volume method, both experimental setups were modelled taking heat transfer effects into account. As a result, the Taylor-Quinney coefficient is calculated by means of experimental data. It is shown that the Taylor-Quinney coefficient is a variable value depending on the flow behaviour of the steel. The local strain rate and the specimen geometries of Marciniak test have a significant influence on the arising heat conduction. The stress state, however, has minor influence on β.

Organisationseinheit(en)
Institut für Umformtechnik und Umformmaschinen
Typ
Konferenzaufsatz in Fachzeitschrift
Journal
Procedia Manufacturing
Band
29
Seiten
464-471
Anzahl der Seiten
8
Publikationsdatum
2019
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Wirtschaftsingenieurwesen und Fertigungstechnik, Artificial intelligence
Elektronische Version(en)
https://doi.org/10.1016/j.promfg.2019.02.163 (Zugang: Offen)
 

Details im Forschungsportal „Research@Leibniz University“