A Novel Probabilistic Fatigue Life Prediction Method for Welded Structures Based on gPC

Abstract

The traditional fatigue life prediction methods based on the S-N curve all believe that the parameters in the model are deterministic constants and can be categorized to the deterministic life prediction. However, in practice, it is difficult to carry out a large number of experiments due to the limitation of time or the possible shortage of funds. In addition, the specimens used in the experiments are not exactly the same, and the test operations and data reading depend on the accuracy of the test equipment as well as the subjective judgment of the testers, which result to the uncertainty of the S-N curve. Therefore, the uncertainty should be considered in order to improve the accuracy of the fatigue life prediction. In this paper, the uncertain factors affecting the fatigue life of welded joints are summarized, and the generalized polynomial chaos (gPC) is introduced into fatigue life prediction. A novel probabilistic fatigue life prediction method combined with the nonlinear cumulative damage model considering the uncertainty of the S-N curve is constructed. An illustrative example is presented to demonstrate the advantages of the proposed approach.

Tailoring the Fatigue Detail Category Class: A Deterministic Implementation of a Probabilistic-Based Approach to Consequence- and Uncertainty-Informed Fatigue Life Prediction of Ships

“…A detailed overview is given in [11,12]. A probabilistic approach to fatigue design of steel-welded structures is applied by [13][14][15][16][17][18], amongst others. Chryssanthopoulos [13] applies the (Basquin-type) S-N curve approach, using probabilistic formulations to improve the estimate of the probability and size of the initial crack for the fracture mechanics approach.…”