Abstract:
This paper presents a sequential approach used in fatigue life prediction of a low pressure steam turbine
blade during resonance conditions encountered during a turbine start-up by incorporating probabilistic
principles. Material fatigue properties are determined through experimental testing of used blade material
X22CrMoV12-1 along with statistical modelling using regression analysis to interpret the stress-life
diagram. A finite element model of a free-standing LP blade is developed using the principle of substructuring
which enables the vibration characteristics and transient stress response of the blade to be
determined for variations in blade damping. Random curve fitting routines are performed on the fatigue
and FEM stress data to ensure that the selection of the random variables used in fatigue life calculations is
stochastic in nature. The random vectors are selected from a multivariate normal distribution. The use of
confidence intervals in the probabilistic fatigue life model works effectively in being able to account for
uncertainty in the material fatigue strength parameters and varying stress in the blade root. The predicted
fatigue life of the blade is shown to be in good agreement with discrete life modelling results.
