New Attraction Term for the Soave‐Redlich‐Kwong Equation of State
Bibliographic record
Abstract
Abstract A new 3‐parameter attraction term for the Soave‐Redlich‐Kwong equation of state, that ensures a correct physical behaviour, is proposed to improve its predictive capabilities, particularly in the supercritical region and in the gas phase. Vapour pressure and second virial coefficient data for a set of eight pure fluids with a low acentric factor ω (Ar, Ne, Kr, O2, N2, C‐H4, CO and C2‐H6) are used to determine the equation's adjustable parameters. When only vapour pressure data are considered the supercritical region is poorly described. An extension of the data base by including for instance the second virial coefficient data leads to a significant improvement in the description of the sub and supercritical regions of the considered fluids and particularly in the prediction of the Joule‐Thomson inversion curves. The new attraction term is shown to be suitable for other pratical fluids like hydrocarbons as well as their mixtures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".