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One of the most important input data in fatigue analysis is the material fatigue properties. This research aims to present a methodology for assessment of statistical planning of fatigue experiments through a MatLab algorithm developed based on Monte Carlo simulations, which enables to simulate statistically the effects of main parameters used for defining the fatigue test setting and to verify their impact on the relative percentage difference (RPD) in fatigue properties estimation comparing to a reference material. The aspects treated here have not been clearly discussed in the standards. Therefore, the proposed recommendations combined with standards procedures is a tool for test engineers, permitting a fatigue test planning with more background and precision, which can help in decisions about which is the better setup, including the sample size, number of stress levels, stress value in each level, and replication. The methodology and good practices presented in this paper were demonstrated by means of actual data from the literature.

This paper introduces a hybrid approach for obtaining S-N curves with reduced number of tests associated to statistically simulated data. In order to validate the proposal, two validation process were developed. One using a methodology to generate S-N curves based on Monte Carlo simulations and other using actual data according Zhao et al. 1998 , allowing to compare the hybrid approach with the experimental curve S-N obtained with high replication. In both validation process, a good accuracy was verified. Subsequently, the fatigue analysis of a fillet welded joint was carried out using finite element analysis to evaluate the cumulative damage and fatigue life, enabling comparison between the proposed method and standard NBR 8800 2008. The results obtained with the proposed methodology allowed more accuracy results and less conservative than standard for the same weld detail class, both for fatigue life and for cumulative fatigue damage evaluations.

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