Application of adaptive neuro-fuzzy inference system in modeling fatigue life under interspersed mixed-mode (I and II) spike overload

In service components and structures frequently come across complicated fatigue loading situations such as interspersed mixed-mode (I and II) spike load on subsequent mode-I fatigue crack growth. The designers rely on different fatigue life prediction methodology in order to avoid costly and time consuming fatigue tests. Earlier authors' have proposed exponential and ANN models to predict the fatigue life of 7020 T7 and 2024 T3 Al alloys under the above loading conditions. In the present work, an attempt has been made to predict the fatigue life by adopting adoptive neuro-fuzzy inference (ANFIS) technique. It is observed that the predicted results for both the alloys are within the maximum range of 0.05% in comparison to experimental findings.

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