A Probabilistic Model for LCF

TL;DR

This paper introduces a probabilistic model for low-cycle fatigue in polycrystalline metals that accounts for size effects and inhomogeneous strain fields using a Poisson point process, providing a more physical interpretation of CMB parameters.

Contribution

The paper presents a novel probabilistic model for LCF that incorporates size effects and strain inhomogeneity, with a new interpretation of CMB parameters based on specimen geometry.

Findings

Model successfully calibrated with LCF test data of RENE 80 specimens.

Model captures size effects and strain field inhomogeneities in fatigue life predictions.

Validation shows improved accuracy over traditional deterministic approaches.

Abstract

Fatigue life of components or test specimens often exhibit a significant scatter. Furthermore, size effects have a non-negligible influence on fatigue life of parts with different geometries. We present a new probabilistic model for low-cycle fatigue (LCF) in the context of polycrystalline metal. The model takes size effects and inhomogeneous strain fields into account by means of the Poisson point process (PPP). This approach is based on the assumption of independently occurring LCF cracks and the Coffin-Manson-Basquin (CMB) equation. Within the probabilistic model, we give a new and more physical interpretation of the CMB parameters which are in the original approach no material parameters in a strict sense, as they depend on the specimen geometry. Calibration and validation of the proposed model is performed using results of strain controlled LCF tests of specimens with different surface areas. The test specimens are made of the nickel base superalloy RENE 80.