In this paper the thermomechanical fatigue properties of 1.4849 cast steel, which is used for exhaust manifolds and turbochargers, are investigated and a fracture mechanics based approach is used for fatigue life prediction. Isothermal low-cycle fatigue tests and thermomechanical fatigue tests are conducted in the temperature range from room temperature up to 1 000 °C. Fractographic investigations show that fracture occurs predominantly intergranularly at 600 °C, whereas mixed transgranular and intergranular crack growth is found otherwise. The methodology for fatigue life prediction is based on a time and temperature dependent cyclic plasticity model, which describes the transient stresses and strains, and on a law for time and temperature dependent microcrack growth. The crack growth law assumes that the increment in crack length in each cycle, da/dN, is correlated with the cyclic crack-tip opening displacement, δCTOD. An analytical fracture mechanics based estimate of δCTOD is used, which is derived for non-isothermal loadings. The fatigue lives of the low-cycle and the thermomechanical fatigue tests are predicted well with the model. Only predictions for the low-cycle fatigue tests at 600 °C, where integranular fracture is predominant, are non-conservative.
The present paper aims to describe the engineering durability design methodology as developed by BMW of hot power train components for both the gasoline cylinder head in aluminium alloys and the hot end components in iron based alloys under thermomechanical fatigue (TMF) conditions. The deformation is described using a viscoplastic model, which in the case for the aluminium alloys is combined with an aging model. The local damage evolution is modelled based on the growth of microcracks with a parameter derived from the J-Integral. Cyclic isothermal and non-isothermal fatigue tests were conducted in order to calibrate the lifetime model. The complexity was limited to a level that the main effects were captured but the analysis of a complex structure was still feasible. The accurate prediction of the variable temperature field is crucial for the success; in the CAE environment the temperature assessment remains the largest uncertainty. An outlook to new upcoming power train components is given.
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