Water content of light n‐alkanes: New measurements and cubic‐plus‐association equation of state modeling
Bibliographic record
Abstract
Light hydrocarbon gases such as methane, ethane, propane, and butane or other so called gaseous solvents have been suggested as steam additives to improve bitumen recovery and energy efficiency. The water content of these gases is one of the key requirements in the simulation and design of solvent‐aided thermal heavy oil recovery processes. In this work, we present new experimental data for the water content of these gases at high temperatures (up to 493.15 K) and moderate pressures (P < 6 MPa). The experimental data was regenerated using the cubic‐plus‐association equation of state. The Soave–Redlich–Kwong equation of state is used to treat the physical interactions. The association interactions are captured using Wertheim's first‐order thermodynamic perturbation theory. A set of binary interaction parameters is proposed to calculate the water content of methane, ethane, propane, and n‐butane at the operating conditions of the thermal heavy oil and bitumen recovery processes. © 2016 American Institute of Chemical Engineers AIChE J, 63: 1384–1389, 2017
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".