Visualizing Interactions Between Liquid Propane and Heavy Oil
Bibliographic record
Abstract
Abstract In this study, we use a custom-designed visual cell to investigate nonequilibrium interactions between liquid propane (C3(l)) and a heavy oil sample (7.2 deg API) at varying experimental conditions. We inject C3(l) into the visual cell containing the heavy oil sample (pressure-buildup process) and allow the injected C3(l) to interact with the oil sample (soaking process). We measure visual-cell pressure and visualize the C3/heavy oil interactions during the pressure-buildup and soaking processes. Nonequilibrium interactions occurring at the interfaces of C3(l)/heavy oil and C3(l)/C3(g) are recorded with respect to time. The results show that the complete mixing of heavy oil with C3(l) occurs in two stages. First, upward extracting flows of oil components from bulk heavy oil phase toward C3(l) phase form a distinguished layer (L1) during the soaking process. The extracted oil components become denser over time and move downward (draining flows) toward the C3(l)/heavy oil interface due to gravity. The gradual color change of L1 from colorless (color of pure C3(l)) to black suggests the mixing of oil components with C3(l). After L1 appears to be uniform, a second layer (L2) is formed above L1 in the bulk C3(l) phase. Extracting and draining flows become active once again, leading to the mixing of oil components from L1 into L2. At final conditions, heavy oil and C3(l) appear to be mixed and form a single uniform phase.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".