Comparison of Models to Data for Phase Equilibria and Properties of CO <sub>2</sub> + Contaminant Systems
Bibliographic record
Abstract
With interest in carbon capture technology and pipelines growing all the time, the properties and phase equilibria of CO 2 and typical CCS flue gas contaminants, such as N 2 , O 2 , and H 2 , among others, need to be estimated with as much accuracy as possible. However, this has to be balanced with the common models used in process simulation. After the book published by Carroll [1], which discusses the accuracy of phase equilibria and the density and viscosity of CO 2 and some mixtures, several recent publications have compared models to experimental data with varying results for physical and transport properties and phase equilibria. This work presents a summary of some of these results and compares the results to a common property package in well-known process simulation software so that process design engineers can establish how accurate their calculations might be, the effects on capture technology and pipeline design, and how much margin may be required.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".