HYDRATE DISSOCIATION CONDITIONS AT HIGH PRESSURE: EXPERIMENTAL EQUILIBRIUM DATA AND THERMODYNAMIC MODELLING
Bibliographic record
Abstract
The past decade has witnessed dramatic changes in the oil and gas industry with the drilling and production extending into progressively deeper waters and higher operating pressures, therefore making it essential to gain a better understanding of the behaviour of gas hydrate at high pressure conditions. New experimental 3-phase H−LW−V (Hydrate−Liquid Water−Vapour) equilibrium data for nitrogen and H−LW−V (Hydrate−Liquid Water−Vapour) and H−LW−LHC (Hydrate−Liquid Water−Liquid Hydrocarbon) data for ethane and propane simple clathrate hydrates were generated by a reliable fixed-volume, isochoric, step-heating technique. The accuracy and reliability of the experimental measurements are demonstrated by comparing measurements with reliable literature data from different researchers. Additional experimental data up to high pressure (200 MPa when available) for CH4, C2H6, C3H8, i-C4H10, N2, Ar, Kr, Xe, H2S, O2, CO and CO2 clathrates have been gathered from literature. The Valderrama modification of the Patel-Teja (VPT) equation of state combined with non-density-dependent (NDD) mixing rules is used to model the fluid phases with previously reported binary interaction parameters. The hydrate-forming conditions are modelled by the solid solution theory of van der Waals and Platteeuw. Langmuir constants have been calculated by both Kihara potential as well as direct techniques. Model predictions are validated against independent experimental data and a good agreement between predictions and experimental data is observed, supporting the reliability of the developed model.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".