Bayesian analysis of fatigue data with multi-load-level damage accumulation : the benefits of rerun specimens
Väntänen, Miikka; Vaara, Joona; Kemppainen, Jukka; Frondelius, Tero (2020-04-07)
Miikka Väntänen, Joona Vaara, Jukka Kemppainen, Tero Frondelius, Bayesian analysis of fatigue data with multi-load-level damage accumulation: The benefits of rerun specimens, International Journal of Fatigue, Volume 138, 2020, 105601, ISSN 0142-1123, https://doi.org/10.1016/j.ijfatigue.2020.105601
© 2020 Elsevier Ltd. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.
https://creativecommons.org/licenses/by-nc-nd/4.0/
https://urn.fi/URN:NBN:fi-fe2020111290015
Tiivistelmä
Abstract
A hierarchical Bayesian approach to analysing fatigue test data including reinserted specimens is proposed. It is found that the inference model is capable of fitting the fatigue damage model to the observed data well. After the addition of rerun specimen data, the results show a significant change in the predictive SN curves. For the analysed 40CrMo8 fatigue data sets, the deviation of fatigue limit is the primary explanatory mechanism for the observed fatigue life scatter. The change of predictive fatigue limit distribution after the addition of rerun data is compared to the change due to additional (simulated) virgin specimen tests.
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