Cast aluminium alloy components are being increasingly used in transport applications
where they may experience cyclic in-service loading. A quantitative prediction of
fatigue performance is required during the component design stage to ensure
components have the necessary lifespan at minimum weight. A multiscale, through
process modelling methodology was developed to calculate fatigue life of cast
aluminium alloy components. This technique first predicts the microstructure and
porosity formation during casting. These features are then tracked through the
subsequent processing steps of heat treatment and finish machining where the residual
stresses are predicted. Finally, all of this informafion is passed to a model for the
prediction of the component's in-service performance. The final fatigue behaviour is
then predicted as a function of the microstructural features, the residual stress state,
and the cyclic in-service loading. To test this methodology, the fatigue life of an A356-
T6 automotive wheel was predicted and then validated experimentally.
Prior authors have found that pores dominate fatigue life in cast A356-T6 if their size
is larger than the secondary dendrite arm spacing. The pore size distribution (and
secondary dendrite arm spacing) in the A356 wheel formed during casting, the first
processing step, was predicted using model-based consfitutive equations run within a
validated macroscopic heat flow model of the process. These results were validated
using x-ray microtomography.
During heat treatment, the second processing step, large residual stresses evolve in the
wheel during quenching. These stresses were predicted using a two-stage thermal
stress model. The results were found to be sensitive to the flow stress data of the A356
alloy. Therefore, the inelastic behaviour in the as-solutionised condition was measured
as a function of temperature and strain rate. Using the measured data significantly
improved residual stress predictions. The release of residual stress during the third
processing step, machining, was then determined.
The influence of both microstructural features and residual stress state was incorporated into the in-service model for final fatigue life prediction. This infiuence
was quantified using x-ray microtomography of interrupted fatigue test specimens.
Local stress concentration analysis was performed to determine the effect of 3D pore
characteristics upon fatigue damage evolution.
Applying the full multiscale, through process model to the A356-T6 wheel, the
location of fatigue crack initiation and fatigue life were accurately predicted. Fatigue
life was most influenced by applied loads, followed by pore size and then residual
stresses.