Phase Behavior and Thermophysical Properties of Propane–Bitumen Mixtures Near Saturation Pressure: Implications for Solvent-Aided Recovery
Bibliographic record
Abstract
Solvent-assisted recovery methods offer a promising alternative to conventional thermal techniques, particularly in reducing environmental impacts and energy intensity. This study investigates the liquid–liquid equilibrium behavior and thermophysical properties of propane–bitumen mixtures under conditions near the saturation pressure of propane. Experimental measurements were conducted across a temperature range of 323.15 to 353.15 K, pressures from 2.00 to 3.43 MPa, and propane feed concentrations between 30 and 50 wt %. Measured properties include the density and viscosity of both liquid phases (except heavy phase viscosity at lower temperatures), propane concentration in each phase, bubble point pressures, and yield. Phase separation and bubble point data were used to construct a P x envelope identifying homogeneous, vapor–liquid, and liquid–liquid regions. Furthermore, gel permeation chromatography was used to analyze the molecular weight distribution of both light and heavy cuts. A thermodynamic model based on the Cubic Plus Association equation of state was developed and tuned using experimental data, and its predictive capability was evaluated against the measured data. The results provide valuable insights into the behavior of propane–bitumen systems under conditions relevant to solvent-assisted in situ recovery.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".