Appl. Mech., Volume 1, Issue 4 (December 2020) – 2 articles

Fatigue lifetime of offshore pipelines with semi-elliptical circumferential surface cracks is often underestimated. An accurate prediction of the pipeline structural integrity is nevertheless important in order to prevent unnecessary and expensive downtime, failures leading to leakage or spillage of pipeline contents to the surrounding environment, and ultimately improve the reliability of the pipeline. The estimation of crack growth in pipelines under varying loads is highly dependent on the calculation of crack driving parameters, such as the stress intensity factor and the crack tip opening displacement (CTOD) using the 3D J-integral or its equivalent. This paper presents a numerical study to predict the fatigue lifetime of cracks in pipes, determining the J-integral that includes first and second derivatives of the displacement field for pipes containing a range of circumferential surface cracks. A pipe segment is structurally loaded and stress intensity factors (SIF) evaluated using the finite element method (FEM). Based on the results, a number-of-cycles to failure curve shows a longer lifetime than previously predicted by about 5% for a pipe with semi-elliptical external surface cracks. In addition, they indicate that the external short cracks are more dangerous than the internal long surface crack hereby requiring earlier assessment. Full article

Digital image correlation (DIC) systems have been used in many engineering fields to obtain surface full-field strain distribution. However, noise affects the accuracy and precision of the measurements due to many factors. The aim of this study was to find out how different filtering options; namely, simple mean filtering, Gaussian mean filtering and Gaussian low-pass filtering (LPF), reduce noise while maintaining the full-field information based on constant, linear and quadratic strain fields. Investigations are done in two steps. First, linear and quadratic strain fields with and without noise are simulated and projected to discrete measurement points which build up strain window sizes consisting of $6\times 5$, $12\times 11$, and $26\times 17$ points. Optimal filter sizes are computed for each filter strategy, strain field type, and strain windows size, with minimal impairment of the signal information. Second, these filter sizes are used to filter full-field strain distributions of steel samples under tensile tests by using an ARAMIS DIC system to show their practical applicability. Results for the first part show that for a typical $12\times 11$ strain window, simple mean filtering achieves an error reduction of 66–69%, Gaussian mean filtering of 72–75%, and Gaussian LPF of 66–69%. If optimized filters are used for DIC measurements on steel samples, the total strain error can be reduced from initial 240−300 $\mu$strain to 100–150 $\mu$strain. In conclusion, the noise-floor of DIC signals is considerable and the preferable filters were a simple mean with $\overline{s^{*}}$ = 2, a Gaussian mean with $\overline{{\sigma }^{*}}$ = 1.7, and a Gaussian LPF with $\overline{D_0^{*}}$ = 2.5 in the examined cases. Full article