The stress intensity factor (SIF) and the degree of bending (DoB) are among the crucial parameters in evaluating the fatigue reliability of offshore tubular joints based on the fracture mechanics (FM) approach. The value of SIF is a function of the crack size, nominal stress, and two modifying coefficients known as the crack shape factor (Yc) and geometric factor (Yg). The value of the DoB is mainly determined by the joint geometry. These three parameters exhibit considerable scatter which calls for greater emphasis in accurate determination of their governing probability distributions. As far as the authors are aware, no comprehensive research has been carried out on the probability distribution of the DoB and geometric and crack shape factors in tubular joints. What has been used so far as the probability distribution of these factors in the FM-based reliability analysis of offshore structures is mainly based on assumptions and limited observations, especially in terms of distribution parameters. In the present paper, results of parametric equations available for the computation of the DoB, Yc, and Yg have been used to propose probability distribution models for these parameters in tubular Kjoints under balanced axial loads. Based on a parametric study, a set of samples were prepared for the DoB, Yc, and Yg; and the density histograms were generated for these samples using Freedman-Diaconis method. Ten different probability density functions (PDFs) were fitted to these histograms. The maximum likelihood (ML) method was used to determine the parameters of fitted distributions. In each case, Kolmogorov-Smirnov test was used to evaluate the goodness of fit. Finally, after substituting the values of estimated parameters for each distribution, a set of fully defined PDFs were proposed for the DoB, crack shape factor (Yc), and geometric factor (Yg) in tubular K-joints subjected to balanced axial loads.
KeywordsTubular K-joint; degree of bending (DoB); stress intensity factor (SIF); geometric factor; crack shape factor; probability density function (PDF); Kolmogorov-Smirnov goodness-of-fit test.