Phase Behavior and Thermophysical Properties of Peace River Bitumen + Propane Mixtures from 303 K to 393 K
Bibliographic record
Abstract
Propane and mixtures including propane as a principal component are among the leading potential candidates for co-injection along with steam for improving the process and environmental efficiency of oil sands bitumen production processes. Phase diagrams and thermophysical property data enable technologies for the development and optimization of such processes. In this work, phase behavior, phase composition, and phase densities of propane + Peace River bitumen mixtures are reported in the temperature range 303 to 393 K at pressures ranging from 1 to 6 MPa. The phase behavior of this pseudobinary mixture can be categorized as Type III according to the van Konynenburg–Scott nomenclature. Pressure–temperature at fixed composition, and pressure–composition at fixed temperature phase diagrams, and pressure–temperature phase projections are presented, along with saturated compositions and densities of the coexisting bitumen-saturated propane liquid (L 1 ) and propane-saturated bitumen liquid (L 2 ) phases. Saturated L 1 and L 2 phases are both significantly less dense than liquid water phases at the same temperatures and pressures, and the volumes of mixing, particularly for the L 1 phase, are large and negative. This data set provides a benchmark for process development and process design calculations for ongoing bitumen production and deasphalting applications.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".