Session: MF-08-01/10-01 Development of Stress Intensity Factor Solutions (Joint with C&S) and Pipeline Integrity

Paper Number: 62038

Start Time: Wednesday, July 14, 2021, 09:00 AM

62038 - Fatigue Crack Growth Rate Data Assessment 

A comprehensive fatigue test database was developed in PRCI SIA-1-1 and IM-3-2 projects, where there are 185 sets of fatigue crack growth rate parameters (i.e., C and m fitting coefficients in Paris’ law) calculated from compact tension (CT) fatigue test data. Four sets of recommended values of C and m were presented for two flaw locations (BM and ERW) and two R ratios (R < 0.5 and > 0.5). The past works did not further assess the fatigue crack growth rate data (i.e., C and m), although intuitively, two parameters should be correlated. To this end, a systematic study was carried out to reassess the fatigue crack growth rate database. It is found that parameters C and m are strongly correlated in the form of m = A*log(C) + B, where A and B are fitting coefficients. In addition, C and m (m_residual) values follow lognormal and normal distributions, respectively, where m_residual refers to the residual of predicted values. The values of A and B for BM or ERW at R = 0.1 or 0.6 (four scenarios) are reported. Note that the distributions of C and m for ERW cases have relatively heavier tails and shorter peaks.

 

Based upon newly developed four sets of A and B values, a series of probability studies were carried to calculate the most-likely fatigue life in the integrity analysis. Note that two ERW pipe segments reported in PRCI SIA-1-1 and IM-3-2 projects were considered in the full-scale test, where fifty-one (51) initial notches were prepared to evaluate the fatigue crack growth rate. The initial notches include different crack lengths, depths, materials, and flaw locations (e.g., BM and ERW seam). The fatigue crack growths calculated from the PRCI approach were used as the baseline for comparisons. In total, 30,000 pairs of C* and m* data points were generated from random sampling for each scenario, and there are over 1.5 million random simulations carried out. The probability densities for each full-scale test case were simulated using a Monte-Carlo approach. The fatigue life distributions for BM is relatively narrow because of the lower standard deviation of the fatigue crack growth rate parameters. On the other hand, the fatigue life distributions for ERW is relatively wider than those for BM. The most-likely (median) fatigue life from the probabilistic study is almost identical to fatigue life from deterministic calculations for the BM cracks. The probabilistic simulation results of ERW seam crack fatigue lives are significantly different from those for BM cracks.

Presenting Author: Enyang Wang BMT Canada

Authors:

Enyang Wang BMT Canada
Aaron Dinovitzer BMT Canada
Sanjay Tiku BMT Canada