Development of a probabilistic model for the prediction of fatigue life in the very high cycle fatigue (VHCF) range based on inclusion population

¹ Institut für Werkstofftechnik, Universität Siegen, 57068 Siegen, Germany
² Department Mathematik, Universität Siegen, 57068 Siegen, Germany
³ Institut für Werkstoffwissenschaft, TU Dresden, 01069 Dresden, Germany

^a Corresponding author: e-mail: anton.kolyshkin@uni-siegen.de

Abstract

The VHCF behaviour of metallic materials containing microstructural defects such as non-metallic inclusions is determined by the size and distribution of the damage dominating defects. In the present paper, the size and location of about 60.000 inclusions measured on the longitudinal and transversal cross sections of AISI 304 sheet form a database for the probabilistic determination of failure-relevant inclusion distribution in fatigue specimens and their corresponding fatigue lifes. By applying the method of Murakami et al. the biggest measured inclusions were used in order to predict the size of failure-relevant inclusions in the fatigue specimens. The location of the crack initiating inclusions was defined based on the modeled inclusion population and the stress distribution in the fatigue specimen, using the probabilistic Monte Carlo framework. Reasonable agreement was obtained between modeling and experimental results.