Anna-Maija Arola, Antti Kaijalainen, Vili Kesti, A-P. Pokka, Jari Larkiola, Digital image correlation and optical strain measuring in bendability assessment of ultra-high strength structural steels, Procedia Manufacturing, Volume 29, 2019, Pages 398-405, ISSN 2351-9789, https://doi.org/10.1016/j.promfg.2019.02.154
Digital image correlation and optical strain measuring in bendability assessment of ultra-high strength structural steels
|Author:||Arola, Anna-Maija1; Kaijalainen, Antti1; Kesti, Vili2;|
1University of Oulu, B.O.Box 4200, FI-90014 University of Oulu, Finland
2SSAB Europe, Rautaruukintie 155, 92101 Raahe, Finland
|Online Access:||PDF Full Text (PDF, 1.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2018080933578
|Publish Date:|| 2019-04-23
Air-bending is a widely used forming process for ultra-high strength steel because it is fast, cost-effective and flexible way to form material. The bendability of a material can be expressed by minimum bending radius R/tmin, which is the relation of the smallest inner radius to the sheet thickness the material can be bent without damage. Damage usually occurs on the outer surface of the bend in the form of intense strain localization that further progresses to cracking. The minimum bending radius contains no other information that affects the bendability such as the lower tool width or the desired bending angle. Hence, developing more detailed test procedure is critical to better describe the behavior of ultra-high strength steel sheet in bending. In this paper, a method for more detailed assessment of bendability for ultra-high strength structural steel is presented. Using optical strain measuring techniques and digital image correlation coupled with bending tests in a universal tensile test machine one can measure the strain evolution at the outer surface of the bend and determine the critical strains that limit the bendability of these materials.
|Pages:||32 - 50|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
216 Materials engineering
The authors of this paper would like to acknowledge the support of Business Finland and SSAB.
© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the organizing committee of SHEMET 2019. https://doi.org/10.1016/j.promfg.2019.02.154.