Abstract
This work deals with the prediction of time-to-rupture (TTR) diagrams of martensitic 9-
12% Cr steels. Martensitic 9-12% Cr steels are state of the art materials for powerplants due to their
high creep strength and oxidation resistance. Since the experimental determination of TTR diagrams
is costly and time-expensive (minimum 10 years), it is of particular interest to be able to model TTR
diagrams and gradually replace experiments.
Here, we approach the question to what extent we can generate a TTR diagram of a material out
of a fraction of experimental results plus detailed understanding of the underlying
microstructural/physical phenomena during creep. Our model is based on dislocation creep and
includes multiple interactions between the microstructural constituents.
We show the applicability of our approach by reproducing a TTR diagram of the well-known
material P92. Input parameters are basic material data from literature, the starting microstructure
before creep, chemical composition, some model parameters determined on the similar material P91,
and one single creep curve of P92. The precipitate evolution is simulated by the software MatCalc,
the other microstructural constituents (dislocation densities, subgrain boundaries etc.) by our creep
model. By varying the stress between individual creep simulations whilst keeping all input parameters
(starting microstructure, temperature and material parameters) constant, we produce multiple creep
curves and thus generate the complete dataset for a TTR diagram.
The model is of particular interest when it comes to the development of new materials, as the
application range of these materials can be estimated quickly and with good reproducibility.
| Original language | English |
|---|---|
| Pages (from-to) | 159-165 |
| Number of pages | 7 |
| Journal | Materials Science Forum |
| Volume | 1105 |
| DOIs | |
| Publication status | Published - 2023 |
Fields of science
- 203 Mechanical Engineering
- 203007 Strength of materials
- 203024 Thermodynamics
- 203034 Continuum mechanics
- 211103 Physical metallurgy
- 211105 Nonferrous metallurgy
- 101014 Numerical mathematics
- 101028 Mathematical modelling
- 102001 Artificial intelligence
- 102022 Software development
- 103006 Chemical physics
- 103018 Materials physics
- 103042 Electron microscopy
- 105113 Crystallography
- 203002 Endurance strength
- 203013 Mechanical engineering
- 203037 Computational engineering
- 205019 Material sciences
- 211101 Iron and steel metallurgy
- 103009 Solid state physics
- 103043 Computational physics
JKU Focus areas
- Digital Transformation
- Sustainable Development: Responsible Technologies and Management
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