Abstract
New probabilistic lifetime approaches for coarse grained Ni-base superalloys supplement current deterministic gas turbine component design philosophies; in order to reduce safety factors and push design limits. The models are based on statistical distributions of parameters, which determine the fatigue behavior under high temperature conditions. In the following paper, Low Cycle Fatigue (LCF) test data of several material batches of polycrystalline Ni-base superalloy René80 with different grain sizes and orientation distribution (random and textured) is presented and evaluated. The textured batch, i.e., with preferential grain orientation, showed higher LCF life. Three approaches to probabilistic crack initiation life modeling are presented. One is based on Weibull distributed crack initiation life while the other two approaches are based on probabilistic Schmid factors. In order to create a realistic Schmid factor distribution, polycrystalline finite element models of the specimens were generated using Voronoi tessellations and the local mechanical behavior investigated in dependence of different grain sizes and statistically distributed grain orientations. All models were first calibrated with test data of the material with random grain orientation and then used to predict the LCF life of the material with preferential grain orientation. By considering the local multiaxiality and resulting inhomogeneous shear stress distributions, as well as grain interaction through polycrystalline Finite Element Analysis (FEA) simulation, the best consistencies between predicted and observed crack initiation lives could be achieved.
Highlights
Due to the worldwide increase in fluctuating renewable energy generation, flexibly operating gas turbine power plants are necessary to secure stable power supply and grid frequencies
The results of metallographic examination of the specimen material (Section 3.1) and its implications on the Finite Element Analysis (FEA) modelling (Section 3.2) are described. It follows that different specimen stiffness (Section 3.2) and Schmid factor (Section 3.3) distributions are calculated for the two material batches
The resulting shear stresses at the slip systems τi,j were calculated for both FEA models, using
Summary
Due to the worldwide increase in fluctuating renewable energy generation, flexibly operating gas turbine power plants are necessary to secure stable power supply and grid frequencies. Frequent start-ups and shut downs as well as load changes lead to high requirements to the materials used in the hot gas section components, foremost the turbine blades. Due to their outstanding properties at high temperatures, Ni-base superalloys are appropriate as turbine blade material. [1,2] utilized measured defect size distributions for probabilistic modeling. This approach is used for fatigue prediction of turbine disks [3,4]
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