Compressibility and Rarefaction Effects on Particle Dynamics and Heat Transfer in Aerosol Deposition Process
Bibliographic record
Abstract
The aerosol deposition (AD) method is an emerging coating technique to create a dense ceramic or metal layer on a substrate through the kinetic impaction and cumulative deposition of ultrafine solid particles under near-vacuum conditions. Prediction of the particles’ impact velocity and temperature during the AD process is crucial in enhancing the coating quality. In the present work, a two-way coupled Eulerian-Lagrangian model is developed for an AD system equipped with a converging-barrel nozzle to simulate the supersonic gas flow, particle in-flight behavior, as well as particle conditions upon impact on a flat substrate. The focus of the current study is to understand the effects of compressibility and rarefaction on particle velocity and temperature during the AD process. The effects of compressibility and rarefaction can be assessed using the Mach and Knudsen numbers. Therefore, different models for the drag coefficient and the heat transfer coefficient that take into account the Knudsen, Mach, and Reynolds number effects are implemented into the computational fluid dynamics (CFD) models. The results show that compressibility and rarefaction have significant influence on the particle temperature and velocity. As the particle size reduces, the effects of compressibility and rarefaction become more important.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".