Influence of steam-rich environments on the high temperature tribological behavior of Inconel 718 for sustainable aviation
Why this work is in the frame
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Bibliographic record
Abstract
The aerospace industry has been looking for solutions to minimize emissions of pollutants into the environment. In this direction, replacing fossil fuels is a promising strategy. The use of hydrogen as a fuel has been shown to be a promising alternative due to its cleaner combustion, with the potential to reduce harmful emissions. Hydrogen primarily produces water during combustion, which becomes steam at high temperatures inside a gas turbine engine. However, there is limited research on the behavior of nickel-based alloys, which are widely used in gas turbine engines, in hydrogen and steam-rich environments. The interactions between steam at tribological interfaces within these engines remain poorly studied. Therefore, this study investigates the high temperature tribological behavior of Inconel 718 under steam conditions. Experiments were conducted to understand the wear mechanisms and the effects of temperature and steam on Inconel 718, using an experimental setup for producing and applying superheated steam to the samples during the sliding test. Subsequent analyses were conducted with a 3D measuring laser microscope, scanning electron microscopy (SEM) and Raman spectroscopy. The results revealed that the coefficient of friction decreases with increasing temperature, while wear increases with temperature. Additionally, the presence of steam exhibited a mild influence on wear and friction characteristics.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it