Ensemble In-Flight Particle Diagnostics Under Thermal Spray Conditions
Bibliographic record
Abstract
Abstract The Accuraspray is a new in-flight particle sensor that provides information on the average in-flight particle temperature, using two-color pyrometry, and velocity, using a cross-correlation calculation. Various aspects influencing the reliability of the sensor estimates are studied. First, the sensitivity of the temperature and velocity estimates to the positioning of the sensor with respect to the particle jet, such as the angular orientation of the fibers and the working distance to the spray plume, is evaluated. Then, the influence of the plasma radiation on the temperature measurement is estimated. This influence can be reduced significantly by filtering out the low frequency components of the pyrometric signals, which contain most of the plasma fluctuations. Finally, a lower limit in the signal-to-noise ratio (SNR), for which an acceptable temperature estimate is obtained, is evaluated. A valid velocity estimate can still be obtained with a lower SNR. All these studies were performed under various spraying conditions, including plasma spraying and HVOF, using various feedstock materials (YSZ, Al-Si, cermets).
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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 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".