Metzger, M., Leidenfrost, M., Werner, E., Riedel, H. et al., "Lifetime Prediction of EN-GJV 450 Cast Iron Cylinder Heads under Combined Thermo-Mechanical and High Cycle Fatigue Loading," SAE Int. J. Engines 7(2):1073-1083, 2014, doi:10.4271/2014-01-9047.
This paper reports on the evolution of cracks in the cylinder heads of a large V8 Diesel engine during cyclic engine tests. The observations are compared with the predictions of a lifetime model for combined thermo-mechanical (TMF) and high cycle fatigue (HCF) loading, which is based on a fracture mechanics analysis of microcrack growth in viscoplastic solids and assumes that the crack advance per cycle is proportional to the cyclic crack tip opening displacement. Since the material of the cylinder heads, the cast iron EN-GJV450, exhibits the typical features of cast iron, namely pressure dependence of the yield stress, dilatancy and tension-compression asymmetry, the Gurson model is applied and combined with the viscoplastic Chaboche model. This constitutive model together with the lifetime model is implemented into a finite element code as a user defined material routine. Published model parameters for the considered cast iron are used to carry out the simulation of the engine test. This simulation comprises a CFD analysis to determine the heat transfer coefficients, a thermal analysis of the load cycle and the mechanical analysis. The thermal analysis reproduces the temperatures at various measuring points sufficiently accurately. Finally, the mechanical analysis predicts the location and orientation of the cracks in the valve bridges correctly in all cases. However, the lifetime predictions are rather conservative compared to the tests (by a factor of 1 to 5 in lifetime). This is discussed and explained by the fact that the cracks were detected in the tests only when they had already spread over a substantial fraction of the valve bridge width. To describe this situation a long-crack analysis would be necessary, which is not yet included in the applied lifetime model.