Prediction of mode-I overload-induced fatigue crack growth rates using neuro-fuzzy approach

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摘要

A methodology has been developed to predict fatigue crack propagation life of 7020 T7 and 2024 T3 aluminum alloys under constant amplitude loading interspersed with mode-I spike overload. It has been assessed by adopting adaptive neuro-fuzzy inference system (ANFIS), a novel soft-computing approach, suitable for non-linear, noisy and complex problems like fatigue. The proposed model has proved its efficiency quite satisfactorily compared to authors’ previously proposed ‘Exponential Model’, when tested on both the alloys.

论文关键词:Adaptive neuro-fuzzy inference system,Adaptive network,Delay cycle,Exponential model,Fatigue crack growth rate,Fatigue life,Retardation parameters

论文评审过程:Available online 16 September 2009.

论文官网地址:https://doi.org/10.1016/j.eswa.2009.09.022