Fatigue Tests of Un-notched and Notched Specimens and Life Prediction using A Variable Critical Distance Method 2019-01-0801
Fatigue is one of the most common failure mechanism in the engineering structures. Statistical nature of fatigue life and the stress gradient are the two challenges among many while designing any component or structure for fatigue. Fatigue lives of the same component exhibit the considerable variation under the same loading and other identical operating conditions due to the difference in the material microstructure and other uncontrolled parameters. Consideration of the variation in fatigue life is extremely important for a reliable product design. Stress concentration at the notch causes stress gradient and therefore applying the plane specimen results for actual engineering components with notches does not give qualitatively reliable results if the stress gradient effects are not considered. The objective of the work presented here is to perform the fatigue tests of plane, U and V-notch specimens which were die casted using aluminum alloy (A380) and to perform fatigue life simulation using a variable critical distance method which considers the stress gradient due to the notch geometry. Specimens were prepared in the foundry shop to minimize the micro-structural variations and radiographic study was carried out to ensure that casted specimens have minimum or no porosity. Geometrical variations of the prepared specimens were studied in the Metrology lab to ensure the geometrical tolerances were minimum. Laboratory tests were conducted in the fatigue test lab using plane, U and V-notch specimens at several loads and S-N curves are obtained. A simulation method is proposed to perform fatigue life prediction which considers the effect of different stress gradients due to difference in the notch geometry. A good correlation was obtained between the experimental and simulation results. This method offers a better way for quantitative prediction of fatigue life and could be very helpful to design robust automotive components.
Neeraj Carpenter, Pankaj Jha, Sudipto Ray, Michael D. Nienhuis
General Motors Technical Center India, General Motors Global Propulsion Systems