Fatigue-Life Data

Figure 6.45 Fatigue life data, S-N curves, for a high-strength steel under different environmental conditions. Stress ratio R — — 7. Loading frequency 7 Hz for tests in 0.6 M NaCIsolution. Horizontal arrows indicate failure condition not attained. OCP = open-circuit potential102...

These optimum ratios and fatigue life data should not be considered to be universal values. Different recipes, different types of antidegradants, different... 

The cyclic load limitation for synthetic ropes in the Koepe hoist application is unknown and would require testing to determine an appropriate limit. However, it is known based on existing fatigue life data that high performance synthetic materials have better life compared with steel. Moreover, service life of Koepe hoist ropes is essentially a Bend-Over-Sheave (BOS) and tension-tension fatigue relationship, which are well-known and studied phenomena that are relatively easily simulated and tested, as opposed to drum hoist ropes for which rope life is primarily limited by rope-to-rope interactions on the hoist drum which is difficult to model, test and predict. 

Acceleration Factors. One of the challenges that must be addressed when attempting to employ Eq. 59.9 directly to assess fatigue life is the determination of the plastic strain and the value of the constant yl. It is crucial to remember that the goal of this analysis is to develop an acceleration transform (or acceleration factor) that can be employed to use known fatigue-life data obtained under controlled laboratory conditions to estimate the number of cycles to failure under field conditions. The acceleration factor AF is defined as the ratio of the number of cycles to fail in the field Nfr to the number of cycles to fail in the lab NfL (see Eq. 59.10). 

Based on the fatigue life data of TC21 titanium with EBW in ultra-high cycle fatigue regime, the probability distribution of fatigue life at certain stress level is discussed in Kolmogorov criterion method and the P-S-N curve is obtained by maximum likelihood estimation method, the conclusions are as follows ... 

Fig. 4.25 Weibull Irdn probability plot of the four amplitude fatigue life data...

Cite five factors that may lead to scatter in fatigue life data. 

The depth factor used in the loannides-Harris theory is known to fit fatigue life data for a number of rolling bearing types however, as discussed in [19], its physical meaning is also obscure, and for this reason, Zaretsky et al. [17] abandoned this concept. On the other hand, Ai [20] introduced a different form of the depth factor but did not present an argument to justify his choice. In the present study no depth factor was used. 

Table 3 does not demonstrate a statistically significant difference between material A and materials which do not contain the large particles. It is probable that the high coefficient of variation of the fatigue life data (34.8%) and the relatively small sample size (15) account for the inability to statistically verify the observed effects of very large particles on fatigue life. 

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