Due to the increasing share of volatile renewable energies the demand for flexible turbine operation rises. This new requirement results in a higher lifetime consumption. Therefore, the assessment of the remaining lifetime of gas and steam turbine components becomes increasingly important in service. To ensure safe operation after lifetime extension it is necessary to provide precise methods to evaluate the impact of previous and future operations onto the components and especially the material.

Conventional methods for non-destructive lifetime prediction are based on operational data, metallographic examinations and hardness testing. Especially the hardness testing of service loaded components provides only limited information about the material properties. Much more information can be determined by miniature specimen testing. One of these miniature specimen tests is the small punch technique (SPT). Specimens can be excavated from service loaded components with minor influence onto the structural integrity and functionality. The prediction of results of conventional material tests (tensile and toughness tests) from the SPT can be done by two methods. Firstly, there are empirical correlations which require much effort in calibration due to a strong material dependency. To overcome this disadvantage the second method makes use of inverse finite element analysis (FEA).

This paper focuses on the inverse FEA to calculate the SPT tests and the prediction of the tensile and fracture toughness behavior. For the description of the SPT tests via FEA the hardening rule of Ramberg-Osgood and the damage model of Gursson-Tvergaard-Needleman (GTN) were used. The inverse FEA is an optimization process which determines the parameters of these material models. Nevertheless, the optimization process cannot provide a unique solution for the 12 parameters included in the material model. This results from a dependency between some parameters, which lead to the same solution in the optimization. Hence a novel description of the dependent parameters was developed and implemented within the optimization process. Therefore, an enhanced inverse FEA approach was proposed which provides a fast converging solution for determination of the material model parameters. Based on the inverse FEA parameter set the results of conventional material tests e.g. tensile tests and toughness can be simulated and the material specific properties can be evaluated. Furthermore, the material model with damage approach is suitable to describe and verify the behavior of the digital twin.

Within this study the forged turbine shaft material EN: 27NiCrMoV15-6 was investigated. For comparison purposes SPT tests as well as tensile tests and fracture toughness tests were carried out. In the case of the tensile properties the test and simulation show coincidence in the curve as well as the characteristic values. For the toughness behavior the characteristic value of the test was met by the simulation. As a result, the inverse FEA of the SPT is suitable to predict conventional material properties which are necessary for the design process and calculation of the remaining lifetime.


Improvement of the Inverse Finite Element Analysis Approach for Tensile and Toughness Predictions by Means of Small Punch Technique

Division / Sponsor:
International Gas Turbine Institute (IGTI)

Paper Proceedings: https://asmedigitalcollection.asme.org/GT/GT2020/volume/84058

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