Issue 38

C. Xianmin et alii, Frattura ed Integrità Strutturale, 38 (2016) 319-330; DOI: 10.3221/IGF-ESIS.38.42 324 Stress level Statistical methods ˆ  β c N 95/95 Number of data out of the 95% confidence interval 1 BJPM 321095 279087 132816 1 BCPM 318112 295985 140858 1 BTPM 329156 297991 141813 1 2 BJPM 212586 184774 87933 0 BCPM 207824 186917 88953 0 BTPM 217875 197179 93837 0 3 BJPM 121001 105170 50050 0 BCPM 119321 109461 52092 0 BTPM 124085 112271 53429 0 Table 4 : Estimated parameters of straight lugs fatigue tests under constant amplitude loading based on BJPM, BCPM and BTPM. Figure 3 : Fatigue life distributions under constant amplitude loading based on BJPM, BCPM and BTPM. All the statistical results obtained through the three statistical methods are similar and the probabilistic distributions are very close to each other. Meanwhile, almost all the test data fall into the 95% confidence interval of the probabilistic distribution, indicating that the probabilistic distributions based on the three statistical methods are reasonable and reliable enough. Moreover, the BJPM is more conservative and simple to use, without super parameters, sample size enlarging or resampling. Thus, the test results in the following are processed by BJPM. The fitted values of A 1 , B 1 , A 2 , B 2 in Eq. (7) and Eq. (8) are listed in Tab. 5, where r is the correlation coefficient of the linear fitting. A 1 B 1 A 2 B 2 r 13.2024 -4.8468 12.8190 -4.8468 0.9930 Table 5 : Coefficients of S-N curves. For an arbitrarily stress level S j with constant stress ratio of 0.06, the corresponding statistical parameters, i.e. β and N 95/95 , can be calculated by Eq. (7) and Eq. (8). Then, the probabilistic distribution of fatigue life N j corresponding to S j can be obtained by numerical sampling based on the Weibull distribution, which provides necessary parameters for the fatigue damage and fatigue life prediction under variable amplitude loading.