Thermal conductivity of CO<sub>2</sub> + R1234yf and CO<sub>2</sub> + R1234ze(Z) binary gaseous mixtures at low pressure
Bibliographic record
Abstract
Abstract Chlorofluorocarbons (CFCs) have been phased out under Montreal Protocol of 1987 as a result of ozone depleting potential (ODP). Carbon dioxide owing to the environmental benefits zero ODP, low global warming potential (GWP), no flammability was expected to replace the principal classes of refrigerants. The use of CO2 may require a total redesign of refrigeration units. Hydrofluoroolefins (HFOs) especially R1234yf and R1234ze(Z) has recently proposed as new generation alternative refrigerants. Because of their mildly flammability the mixing of CO2 and HFOs may offer a good alternative to meet the requirement of high cycle efficiency and not dangerous for human beings. A representation for the thermal conductivity of the mixtures of CO2+HFO’s at atmospheric pressure is developed. The thermal conductivity concerning the mixtures was estimated by Sutherland equation type and by Wassiljeva relation modified by Lindsey and Bromley. To apply this procedure the viscosity and thermal conductivity of pure HFC’s substances were established. To obtain these properties the theoretical approach by Mason, Monchick, Filippov and Golubev were used. The data were obtained at temperatures from 250 K to 360 K. The proposed technique was checked by the comparison with the experi-mental thermal conductivity data for the binary mixtures of R134a and R32 and for the triple zeotrop R407C. The agreement is satisfactory.
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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) | 0.002 | 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".