Accelerated Testing Methodology for Long-term Fatigue Life Prediction of Polymer Composites

2010 ◽  
Vol 17 (4) ◽  
pp. 313-335
Author(s):  
Yasushi Miyano, ◽  
Masayuki Nakada, ◽  
Hongneng Cai,
Keyword(s):  
Fatigue Life ◽  
Polymer Composites ◽  
Life Prediction ◽  
Accelerated Testing ◽  
Fatigue Life Prediction ◽  
Testing Methodology

PROBABILITY VERSUS STATISTICAL MODELING: EXAMPLES FROM FATIGUE LIFE PREDICTION

2005 ◽  
Vol 12 (06) ◽  
pp. 535-550 ◽  
Author(s):  
D. GARY HARLOW
Keyword(s):  
Fatigue Life ◽  
Crack Growth ◽  
Life Prediction ◽  
Failure Modes ◽  
Growth Models ◽  
Operating Conditions ◽  
Fatigue Life Prediction ◽  
Probability Modeling ◽  
Probability Analyses

Probability analyses are increasingly being used for reliability and durability assessments for life prediction of engineered components and systems. Nevertheless, many of the current analyses are predominately statistical rather than probabilistic. Fatigue life prediction has historically been based on the safe-life or the crack growth approaches, both of which are empirically based. Consequently, they do not adequately reflect long-term operating conditions, or identify the sources and extent of their contributions to variability. A comparison between probability and statistical approaches for fatigue life prediction is developed herein. Using simple crack growth models, the variability inherent in S-N response can be related to key random variables that are readily identified in the models. The identification and quantification of these variables are paramount for predicting fatigue lives. The effectiveness of probability modeling compared to statistical methodologies is shown through the analysis of an extensive set of S-N data for 2024-T4 aluminum alloy. Subsequently, the probability approach is demonstrated with S-N data for SUJ2 steel, in which two distinct failure modes are operative. Variability associated with manufacturing and material variables are considered. The adoption of this technique to put life prediction on a sound scientific and probabilistic basis is recommended.

A review of creep-fatigue life prediction methods: identification and extrapolation to long term and low strain cyclic loading

1984 ◽  
Vol 83 (3) ◽  
pp. 267-278 ◽  
Author(s):  
G. Cailletaud ◽  
D. Nouailhas ◽  
J. Grattier ◽  
C. Levaillant ◽  
M. Mottot ◽  
...  
Keyword(s):  
Fatigue Life ◽  
Cyclic Loading ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Prediction Methods ◽  
Creep Fatigue
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