Three‐parameter cubic equation of state for pure components of heavy oils
Bibliographic record
Abstract
Abstract A three‐parameter cubic equation of state for pure hydrocarbons is proposed to model PVT properties of heavy hydrocarbons found in heavy oils. Thirty hydrocarbons up to C40 and some commonly found (associated) non‐hydrocarbons in heavy oils have been used to regress the parameters. Predicted results from the proposed equation for the liquid density, vapour pressure, saturated liquid density, and saturated vapour density have been compared with the widely used Peng–Robinson (PR), Soave–Redlich–Kwong (SRK), and Patel and Teja (PT) equations of state. With the increase in carbon number in hydrocarbon, the % average absolute errors in liquid density, vapour pressure, and saturated liquid density prediction using PR, SRK, and PT equations of state were found to increase, whereas the proposed equation shows consistency in the prediction, with a % average absolute error of 2.5% only.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".