Phase Equilibrium Data and Model Comparisons for H<sub>2</sub>S Hydrates
Bibliographic record
Abstract
Hydrogen sulfide is an exceptionally stable structure I (sI) gas hydrate forming guest molecule that is becoming increasingly prevalent in oil and gas production. However, phase equilibria data on pure hydrogen sulfide hydrate reported in the literature are relatively limited and inconsistent compared to other common hydrate formers such as methane or carbon dioxide. In this study, 61 hydrate phase equilibria measurements for sI hydrates containing hydrogen sulfide are reported in the temperature range from T = 273.68 K to 301.53 K and pressure range from p = 0.108 MPa to 1.960 MPa. Experimental data were measured using the isochoric pressure search (IPS) method which has been well established, as well as a modified IPS method, termed the phase boundary dissociation (PBD) method, which gives more efficient measurements of pure hydrate phase equilibria data. For example, it was shown in this work that using the new PBD method reduced the experimental run time to approximately 4.8 h per data point, compared to 40 h to 45 h per data point using the IPS method. The measured data for hydrogen sulfide hydrates were compared with predictions and experimental data reported in the literature, showing agreement between measurements and predictions within an average of 0.08 K for HydraFLASH 2.2 to 1.131 K for PVTSim 21 on average and literature within 0.21 K for Selleck et. al10 to 1.42 K for Carroll and Mather12 on average.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.004 | 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".