Innovative evaluation methods for accelerated provision and assessment of fatigue data using mathematical methods

Increasing demands for resource efficiency as well as cost and time reduction require new innovative approaches in terms of an accelerated and reliable provision of fatigue data. A promising approach is given by the combination of non-destructive testing methods such as IR thermography or electrical resistance with conventional destructive testing (constant amplitude tests and load increase tests). This synergy enables a material-response related evaluation of the material degradation based on a reduced number of specimens. Because of the decreased number of fatigue specimens, a reliable assessment of different failure probabilities becomes challenging, creating a gap between accelerated lifetime prediction and sufficient statistical validation, which must be closed by the integration of mathematical methods. This paper addresses two key research objectives. First, a mathematical and material-independent algorithm is presented which enables an accelerated and automated estimation of the fatigue strength of materials. Besides that, the main focus is on the statistical provision of S–N curve parameters based on existing lifetime prediction methods. Therefore, the quality of virtually determined numbers of cycles to failure is compared with conventionally performed constant amplitude tests. Furthermore, the newly introduced Splitted Parameter Approach enables a quantitative statement to be made regarding the reliability of the parameters of the virtual S–N curve. The presented methods are developed on a 20MnMoNi5-5 steel with a ferritic-bainitic microstructure.