Numerical Study Using Nano-Particles by Varying the Expansion Ratio and Height of Cold Spray Nozzle to Predict Deposition Efficiency
Bibliographic record
Abstract
Abstract The coatings of zinc and its alloys are broadly used to prevent the rusting of substrate surfaces such as steel. Cold gas dynamic spray (CGDS) is an innovative coating technique in which the deposition of solid powder particles depends upon the kinetic energy of the particles rather than thermal energy. Therefore, application of cold spray is to provide superior rust resistance by depositing more materials, formation of passivation layer, and cathodic protection. In this study, numerical investigations on zinc micro and nano size particles in CGDS were carried out. The height of the injector, the expansion ratio and the diameter of the inlet of the de-Laval nozzle was varied systematically by optimizing the stand-off distance using the two-dimensional axisymmetric models of CGDS, to study their effects on the velocity and the distribution of the particles. Prediction of the deposition efficiency was carried out using the various critical and erosion velocity models.
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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 | 0.001 |
| 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".