THERMAL BARRIER COATING FATIGUE LIFE ASSESSMENT

Published By SIEMENS

• By Brodin H., Jinnestrand M. Johansson S. and Sjöström S.
• Published October 2006
• 10 Page(s)

In land-based gas turbines, thermal barrier coatings are used for thermal insulation of hot components (combustor, turbine vanes and to some extent blades). The thermal barrier maintains the metal temperature of a coated component at moderate temperature levels during turbine operation. If the coating spalls off, the underlying metal will suffer from creep damage and oxidation with risk of severe machine damage. Therefore coating integrity must be maintained, putting forward demands on a reliable assessment of coating life. This is especially crucial if a design with long inspection intervals is required. In the present work, plasma-sprayed NiCoCrAlY and NiCrAlY bond coats with an yttria partially stabilised zirconia top coat are studied. At the interface between the metallic bond coat and the ceramic top coat delamination cracks are prone to form upon thermal or/and mechanical cycling. Microstructural evaluations show that interface cracks (within the thermally grown oxide) and interface-near cracks (within the partially stabilised zirconia) contribute to damage development. From microstructural investigations of tested material delamination crack growth data has been recorded. Via a damage measure the recorded crack growth data are coupled to the load condition at the crack tip through FE-modeling. In the present work a fatigue life prediction model has been used based on a Paris law-approach. The model is physically sound in the sense that it takes the local stress-state (from thermal and mechanical loading) into account. By calculation of energy release rate at the crack tip and allowing for mode mixity, the delamination behaviour can be modeled according to observations. Through the fracture mechanics approach the model is general and will therefore be suitable for fatigue life predictions in the presence of thermal as well as mechanical loads. The model is calibrated against and verified for results from fatigue tests. By comparison of model predictions with results from test with different conditions, the model is shown to be capable of predicting results with good accuracy.