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*storniert* Bending fatigue of high strength strip steel at 20 kHz and the influence of defects

Thursday (28.05.2020)
11:50 - 12:10
Part of:

Session .1: Cancelled
Belongs to:
General Topic Cancelled

Bending fatigue of high strength strip steel at 20 kHz and the influence of defects

Jens Bergström1, Mohamed Sadek1, Waqas Tofique2, Alexander Löf2, Chris Millward2

1Department of engineering and physics, Karlstad University

SE-651 88 Karlstad, Sweden

2voestalpine Precision Strip AB

684 92 Munkfors, Sweden





High strength strip steel is used in many applications as in engines and compressors. High precision in dimensional tolerances, good surface finish, high tensile strength and fatigue strength are required. One vital requirement is a high fatigue strength at long life lengths, and, hence, it is related to high cleanness of the steel microstructure with minimal internal or surface defects. One application is the use in flapper valves where high fatigue strength in combination with impact fatigue strength is demanded. A high static strength and adequate damping of valve material are also desired. One concern in characterization of the material is difficulties in obtaining the fatigue strength of the thin high strength strips, and in particular the bending fatigue strength. The present study has its focus on the development of a method to obtain the bending fatigue strength at 20 kHz fatigue load frequency, and to evaluate the influence of defect distribution on the fatigue strength. An ultrasonic 20 kHz test instrument working in resonance along the load train is used, and with a bending fixture and a specimen geometry particularly developed for this purpose. Reference testing in uniaxial fatigue of strip specimens is performed. Evaluation of initiating defect distributions and crack initiation mechanisms as fine granular area (FGA) assessments are made by SEM fractography. LOM and SEM-EBSD microstructure and mechanical characterization are performed. Final analysis of the fatigue strength and its dependence on defect distributions is performed using failure probability statistics.

Dr. Muhammad Waqas Tofique
voestalpine Precision Strip AB
Additional Authors:
  • Prof. Jens Bergström
    Karlstad University
  • Dr. Mohamed Sadek
    Karlstad University
  • Alexander Löf
    voestalpine Precision Strip AB
  • Chris Millward
    voestalpine Precision Strip AB