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Methodology for assessment of statistical planning effects on the S‐N curve determination using Monte Carlo simulations
Author(s) -
Goedel Fábio,
Chamberlain Pravia Zacarias Martin,
Mezzomo Gustavo Prates
Publication year - 2019
Publication title -
fatigue and fracture of engineering materials and structures
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.887
H-Index - 84
eISSN - 1460-2695
pISSN - 8756-758X
DOI - 10.1111/ffe.12957
Subject(s) - monte carlo method , replication (statistics) , matlab , sample size determination , computer science , sample (material) , reliability engineering , stress (linguistics) , statistics , engineering , mathematics , chemistry , chromatography , linguistics , philosophy , operating system
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.