Analytical modeling of oxide thickness variation of metals under high temperature solid-particle erosion
Bibliographic record
Abstract
The paper presents a study of model development for predicting the oxide thickness on metals under high temperature solid-particle erosion. The model is created based on the theory of solid-particle erosion that characterizes the erosion damage as deformation wear and cutting wear, incorporating the effect of the oxide scale on the eroded surface under high temperature erosion. Then the instantaneous oxide thickness is the result of the synergetic effect of erosion and oxidation. The developed model is applied on a Ni -based Al -containing ( Ni – Al ) alloy to investigate the oxide thickness variation with erosion duration of the alloy at high temperatures. The results show that the thickness of the oxide scale on the alloy surface increases with the exposure time and temperature when the surface is not attacked by particles. However, when particles impact on the alloy surface, the oxide thickness is reduced, although oxidation is continuing. This indicates that oxidation does not benefit the erosion resistance of this alloy at high temperatures due to the low growth rate of the oxide.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".