Remaining Fatigue Life Predictions Considering Load and Model Parameters Uncertainty

Abstract

Fatigue-driven damage propagation is one of the most unpredictable failure mechanisms for a large variety of mechanical and structural systems subjected to cyclic and/or random operational loads during their service life. Therefore, monitoring the critical components of these systems, assessing their structural integrity, recursively predicting their remaining fatigue life (RFL), and providing a cost-efficient reliability-based inspection and maintenance (RBIM) plan are crucial tasks. In contribution to these objectives, the authors developed a comprehensive reliability-based fatigue damage prognosis methodology for recursively predicting and updating the RFL of critical structural systems and/or sub-assemblies. An overview of the proposed framework is provided in the first part of the paper. Subsequently, a set of experimental fatigue test data is used to validate the proposed methodology at the reliability component level. The proposed application example analyzes the fatigue-driven crack propagation process in a center-cracked 2024-T3 aluminum plate subjected to a sinusoidal load with random amplitude. Four probabilistic models of increasing load amplitude uncertainty together with damage evolution model parameter uncertainty and measurement uncertainty are considered in this study. The results obtained demonstrate the efficiency of the proposed framework in recursively updating and improving the RFL estimations and the benefits provided by a nearly continuous monitoring system.