Effect of Cycle-Counting Methods on Effective Stress Range and Number of Stress Cycles for Fatigue-Prone Details

Abstract

Two important parameters in fatigue life evaluations of existing steel highway bridges are the number of stress cycles experienced and the effective stress range. The inaccuracies in predicting remaining fatigue life can be attributed to either one of these two parameters. However, the AASHTO guide specification has no provisions for the cycle-counting methods to be used to determine these two parameters. A sensitivity analysis that addresses the effects of cycle-counting methods on the effective stress range and the number of cycles for various fatigue-prone details in both main and secondary bridge members is described. A comparison of five cycle-counting methods (level-crossing counting, peak counting, simple-range counting, mean-crossing-peak counting, and rain-flow counting) by using a simple variable-amplitude strain-time history showed that both the stress range and the number of cycles are sensitive to cycle-counting methods. Two of the most commonly used cycle-counting techniques for highway bridge variable-amplitude loading are the mean-crossing-peak and the rainflow cycle-counting methods. A comparison of the two methods by using field data taken under normal traffic showed that the rainflow cycle-counting method is more conservative than the mean-crossing-peak method. The relationship between the mean-crossing-peak and the rainflow cycle-counting methods was determined in the form of a correlation coefficient and a linear regression line. There is a nearly perfect positive correlation between the two methods. Therefore, values obtained for the effective stress range and the number of cycles by the mean-crossing-peak method can be converted to values for the rainflow method.

Research on a Method for Online Damage Evaluation of Turbine Blades in a Gas Turbine Based on Operating Conditions

“…Therefore, it is imperative to research damage evaluation models and load-handling methods specifically tailored to fluctuating loads. Traditional load handling methods [24][25][26] such as rainflow counting, level-crossing counting, and peak counting require traversing the entire load history and reconstructing the load spectrum to identify the maximum cycles as accurately as possible. As a result, these methods are not suitable for online applications, and the reconstructed load spectrum overlooks the impact of load sequence on life.…”