Probabilistic LCF Risk Evaluation of a Turbine Vane by Combined Size Effect and Notch Support Modeling
For gas-turbine design engineers, this model improves LCF life predictions for components with sharp stress gradients, addressing a known bottleneck in current probabilistic approaches.
This paper presents a combined probabilistic model incorporating both size effect and notch support for low cycle fatigue (LCF) risk assessment of a turbine vane, showing significant improvement in life predictions compared to standard E-N curve methods.
A probabilistic risk assessment for low cycle fatigue (LCF) based on the so-called size effect has been applied on gas-turbine design in recent years. In contrast, notch support modeling for LCF which intends to consider the change in stress below the surface of critical LCF regions is known and applied for decades. Turbomachinery components often show sharp stress gradients and very localized critical regions for LCF crack initiations so that a life prediction should also consider notch and size effects. The basic concept of a combined probabilistic model that includes both, size effect and notch support, is presented. In many cases it can improve LCF life predictions significantly, in particular compared to \textit{E-N} curve predictions of standard specimens where no notch support and size effect is considered. Here, an application of such a combined model is shown for a turbine vane.