A methodology for probabilistic remaining creep life assessment of gas turbine components

Certain gas turbine components operate in harsh environments and various mechanisms may lead to component failure. It is common practice to use remaining life assessments to help operators schedule maintenance and component replacements. Creep is a major failure mechanisms that affect the remaining life assessment, and the resulting life consumption of a component is highly sensitive to variations in the material stresses and temperatures, which fluctuate significantly due to the changes in real operating conditions. In addition, variations in material properties and geometry will result in changes in creep life consumption rate. The traditional method used for remaining life assessment assumes a set of fixed operating conditions at all times, and it fails to capture the variations in operating conditions. This translates into a significant loss of accuracy and unnecessary high maintenance and replacement cost.; A new method that captures these variations described above and improves the prediction accuracy of remaining life is developed. First, a metamodel is built to approximate the relationship between variables (operating conditions, material properties, geometry, etc.) and a creep response. The metamodel is developed using Response Surface Method/Design of Experiments methodology. Design of Experiments is an efficient sampling method, and for each sampling point a set of finite element analyses are used to compute the corresponding response value. Next, a low order polynomial Response Surface Equation (RSE) is used to fit these values. Four techniques are suggested to dramatically reduce computational effort, and to increase the accuracy of the RSE: smart meshing technique, automatic geometry parameterization, screening test and regional RSE refinement. The RSEs, along with a probabilistic method and a life fraction model are used to compute current damage accumulation and remaining life.; By capturing the variations mentioned above, the new method results in much better accuracy than that available using the traditional method. After further development and proper verification the method should bring significant savings by reducing the number of inspections and deferring part replacement.