- Autor
- Krenmayr, Bernhard
- Sonderegger, Bernhard
- TitelPhysical Modeling of dislocation creep in high temperature steels
- Datei
- Erscheinungsjahr2017
- LicenceCC-BY
- Konferenz Name4th International ECCC Creep & Fracture Conference
- Konferenz StaatDeutschland
- Konferenz URLhttp://eccc2017.com/home.html
- Download Statistik919
- Peer ReviewJa
- AbstractIn modern thermal power plants, there is a permanent request for increasing the efficiency and environmental safety. Service temperatures of 600°C and stress levels up to 100 MPa are currently the typical requirements on critical components. The main challenges for the materials involved are a high creep and oxidation resistance in a steam atmosphere for a lifetime of 10+ years. <br/>The most difficult challenge is the save prediction for creep resistance for new materials that can fulfil these requirements. In the past, a wide range of different creep models have been developed to predict this complex behavior. Most of them include a set of fit-parameters to describe and predict the creep behavior of a specific material at a specific condition. Once a set of parameters is set in good accordance to the experimental data, these models can calculate the deformation rate and hence the final lifetime. However, the predictivity of these models is restricted to cases close to the initial training data. Extrapolations beyond this safe range are prone to systematic errors.<br/>For new materials a change in strategy for creep modeling is more promising: the shift from phenomenological to mechanistic approaches. As soon as a model considers actual micro-mechanical phenomena leading to creep deformation and describes the behavior in a physical way without fit-parameters, it is possible to predict deformation rates and life time, as well as indicating the underlying mechanisms. This work aims to give an overview of already existing models, state of the art modeling and considerations about future developments in modeling dislocation creep. The main focus of the discussion is set on the necessary input parameters, the individual sub-models and the requirements for such an approach.<br/>
[1.05 MB]