Title of article :
Prediction of mode-I overload-induced fatigue crack growth rates using neuro-fuzzy approach
Author/Authors :
Mohanty، نويسنده , , J.R. and Verma، نويسنده , , B.B. and Ray، نويسنده , , P.K. and Parhi، نويسنده , , D.R.K.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
Abstract :
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.
Keywords :
Adaptive network , Delay cycle , Fatigue life , Adaptive neuro-fuzzy inference system , Exponential model , Fatigue crack growth rate , Retardation parameters
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications