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Data Fusion and Modeling for Fatigue Crack Growth Prediction
Technical Paper
2007-01-1656
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
A methodology is proposed to reduce the effects of uncertainty in fatigue crack growth investigations, especially for very high cycle fatigue. The approach integrates experimental data with modeling in order to manage the uncertainty with minimal amounts of data. An extensive set of very high cycle fatigue data collected on SUJ2 bearing strength steel will be used to demonstrate the procedure. The fatigue cracks nucleate from internal particles as well as surface damage, both of which can have fatigue lives in excess of 108 cycles. Consequently, it would be advantageous to have a methodology that would predict long term fatigue life with multiple modes of damage growth by infusing limited data with fatigue modeling.
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Authors
Citation
Gary Harlow, D., "Data Fusion and Modeling for Fatigue Crack Growth Prediction," SAE Technical Paper 2007-01-1656, 2007, https://doi.org/10.4271/2007-01-1656.Also In
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References
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- Harlow D.G. Probabilistic Property Prediction Engineering Fracture Mechanics
- Phoenix S.L. Stochastic Strength and Fatigue of Fiber Bundles International Journal of Fracture 13 1978 327 344
- Harlow D.G. Probability Versus Statistical Modeling: Examples from Fatigue Life Prediction International Journal of Reliability, Quality and Safety Engineering 12 2005 535 550