A statistical nonlinear cumulative damage rule and fatigue life prediction under random loading

Abstract

For variable amplitude loading, the fatigue life estimation employing constant amplitude stress-life data and a linear Miner's damage rule is usually nonconservative. Therefore, a plastic work interaction nonlinear damage rule has been proposed to predict a more conservative fatigue life under a countable variable amplitude loading sequence. In the present paper, this nonlinear damage rule is extended to the case of continuous random loading. Order statistics and asymptotic theory of statistical extremes are employed in the analysis. It is concluded that the fatigue life prediction based on this nonlinear damage rule will be reduced by 5 to 20% compared with that based on Miner's rule. The reduction is more obvious under the condition that the plastic work interaction exponent is smaller, the material's fatigue curve slope parameter is smaller, or the number of cycles to failure is larger. These conclusions appear to be reasonable and agree with some available experimental results.