NUMERICAL METHOD FOR DESIGNING A TWO-DIMENSIONAL DE LAVAL NOZZLE FOR OPTIMIZATION IN ASSISTED MACHINING WITH SUPERCRITICAL CO2
Bibliographic record
Abstract
The purpose of this work is to present a quick method for designing the divergent section of planar Laval micro-nozzles in order to predict the properties of the CO2 jet at the nozzle and better control the cooling effect in the context of cryogenic machining with supercritical CO2 (ScCO2). The Method of Characteristics (MOC) and a real gas model have been implemented to obtain 2D nozzles divergent part adapted for single-phase gas expansion. CO2 inlet pressure, inlet temperature, and pressure distribution along the nozzle axis are set as input parameters. A 2D nozzle facility has been developed to allow visualization of the CO2 jet and its expansion in ambient air. Preliminary results are presented to demonstrate the potential of the facility.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".