Notice of RetractionProbabilistic fatigue life prediction of turbine disc considering model parameters uncertainty

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

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Aiming to improve the predictive ability of Walker model for the life of turbine disc and taking an aircraft engine turbine disc made of GH4133 as the application example, this paper investigates the approach on probabilistic fatigue life prediction when considering parameters uncertainty inherent in the life prediction model, i.e. Walker model. Firstly, experimental data are used to update the model parameters with Bayes´ theorem, so as to obtain the posterior probability distribution functions of two model parameters, as well to achieve the probabilistic model for life prediction of turbine disc. During the process of obtaining the posterior distribution, the Markov Chain Monte Carlo(MCMC) technique is employed for generating the samples of the given distribution and estimating the parameters distinctly; Secondly, the turbine disc life is predicted with the Walker probabilistic model by using MC (Monte Carlo) technique. The results show that: (1) under the condition of small scale data for turbine disc, parameters uncertainty of Walker model can be quantified and the corresponding probabilistic model for fatigue life prediction can be established by using Bayes´ theorem; (2) There exists obvious dispersion of life data for turbine disc when predicting fatigue life in practical engineering application, which can be handled and calculated by the different survival rate of prediction life to meet the actual requirements.