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Estimating probabilistic fatigue of Nitinol with scarce samples
, Sivasankar Arul
Published in Elsevier Ltd
2016
Volume: 85
   
Pages: 31 - 39
Abstract
Current work estimates probabilistic fatigue life efficiently with scarce samples. The underlying idea of the estimation is to approximate the cumulative distribution function of the fatigue life in a transformed space using a third order polynomial subject to monotonicity constraint. The variations associated with the estimated quantiles are quantified using bootstrap. The proposed approach is validated on a data obtained from literature. It is observed that the life quantiles with reasonable accuracy can be estimated even with 10 samples. Finally, the probabilistic fatigue of Nitinol in austenitic condition is obtained with limited experiments. © 2015 Elsevier Ltd. All rights reserved.
About the journal
JournalData powered by TypesetInternational Journal of Fatigue
PublisherData powered by TypesetElsevier Ltd
ISSN01421123
Open AccessNo
Concepts (11)
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    Distribution functions
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    Probability
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    Bootstrap
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    Cumulative distribution function
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    MONOTONICITY CONSTRAINT
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    NITINOL
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    PROBABILISTIC FATIGUE
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    QUANTILE
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    Reasonable accuracy
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    THIRD ORDER
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    Fatigue of materials