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.
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 159-165 |
| Seitenumfang | 7 |
| Fachzeitschrift | Materials Science Forum |
| Volume | 1105 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 2023 |
Wissenschaftszweige
- 203 Maschinenbau
- 203007 Festigkeitslehre
- 203024 Thermodynamik
- 203034 Kontinuumsmechanik
- 211103 Metallkunde
- 211105 Nichteisenmetallurgie
- 101014 Numerische Mathematik
- 101028 Mathematische Modellierung
- 102001 Artificial Intelligence
- 102022 Softwareentwicklung
- 103006 Chemische Physik
- 103018 Materialphysik
- 103042 Elektronenmikroskopie
- 105113 Kristallographie
- 203002 Betriebsfestigkeit
- 203013 Maschinenbau
- 203037 Computational Engineering
- 205019 Materialwissenschaften
- 211101 Eisen- und Stahlmetallurgie
- 103009 Festkörperphysik
- 103043 Computational Physics
JKU-Schwerpunkte
- Digital Transformation
- Sustainable Development: Responsible Technologies and Management
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