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An improved neural computing method for describing the scatter of S-N curves
Bučar, Tomaž ; Nagode, Marko ; Fajdiga, Matija
The reliability evaluation of structural components under random loading is affected by several uncertainties. Proper statistical tools should be used to manage the large amount of causalities and ...the lack of knowledge on the actualreliability-affecting parameters. For fatigue reliability prediction of a structural component, the probability distribution of material fatigue resistance should be determined, given that the scatter of loading spectra is known and a suitable damage cumulating model is chosen. In the randomness of fatigue resistance of a material, constant amplitude fatigue test results showthat at any stress level the fatigue life is a random variable. In this instance fatigue life is affected by a variety of influential factors, such asstress amplitude, mean stress, notch factor, temperature, etc. Therefore a hybrid neural computing method was proposed for describing the fatigue data trends and the statistical scatter of fatigue life under constant loading conditions for an arbitrary set of influential factors. To support the main idea, two examples are presented. It can be concluded that the improved neuralcomputing method is suitable for describing the fatigue data trends and the scatter of fatigue life under constant loading conditions for an arbitraryset of influential factors, once the optimal neural network is designed and trained.
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