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Fatigue life prediction of materials can be modeled by deterministic relations, via mean or median S-N curve approximation. However, in engineering design, it is essential to consider the influence of fatigue life scatter using deterministic-stochastic methods to construct reliable S-N curves and determine safe operation regions. However, there are differences between metals and composites that must be considered when proposing reliable S-N curves, such as distinct fracture mechanisms, distinct ultimate strengths under tension and compression loading, and different cumulative fatigue damage mechanisms including low-cycle fatigue. This study aims at conducting a review of the models used to construct probabilistic S-N fields ( P-S-N fields) and demonstrate the methodologies applied to fit the P-S-N fields that are best suited to estimate fatigue life of the selected materials. Results indicate that the probabilistic Stüssi and Sendeckyj models were the most suitable for composite materials, while, for metals, only the probabilistic Stüssi model presented a good fitting of the experimental data, for all fatigue regimes.7

Knowledge of the stochastic nature of fatigue life of composite materials can be modeled by the failure time with the Weibull distribution. This task becomes complex when the samples are small and scattered. In this way, it is necessary to know and to improve robust models of estimation of the parameters of the distribution of Weibull. The aim of this work is to compare the performance of least squares, least squares weighted, maximum likelihood estimator and momentum method and to suggest a method that obtains better performance in life behavior to fatigue with small samples. Monte Carlo simulations were performed to estimate the distribution parameters with different sample sizes and an application with real fatigue data that compares performance using goodness-of-fit. The results of the simulations showed that the weighted least squares estimation was able to generate more reliable estimators for fatigue behavior during its useful life. In this way, it is possible to conclude that small samples make the real representation of life difficult to the material fatigue, but using the weighted least squares estimation method, it is possible to obtain more estimates.

This study aimed to assess the effect of hybridization on thermomechanical properties and water absorption of composite materials, by introducing sisal fiber tissue into the material. To that end, two composite material plates were manufactured, the first with five layers of E-glass reinforcement mat and the second with three layers of E-glass fiber interspersed with two layers of sisal fibers, both used as an orthophthalic polyester resin matrix. The material was then submitted to tensile, three-point bending and water absorption tests. It was observed that hybridization causes a change in both the final strength and stiffness of the material.

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