Development of Graphical Methods for Estimating the Diffusivity Coefficient of Gases in Bitumen from Pressure-Decay Data
Bibliographic record
Abstract
New graphical techniques are presented for estimating the diffusivity coefficient (or mass diffusivity) of CO 2, CH 4, and N 2 in highly viscous bitumens from pressure-decay data. These methods are based on modeling the rate of change in system pressure as gas diffuses into the bitumen using the diffusion equation, coupled with a mass balance for the gas phase. Analytical solutions of the resulting set of equations, with appropriate initial and boundary conditions, are obtained by Laplace transformation. An inverse solution technique is used for developing two graphical methods to estimate the diffusivity coefficient from pressure-decay data reported in the literature. The estimated diffusivity coefficients for gas−bitumen pairs at 75−90 °C vary from 2.5 × 10 - 10 m 2 /s to 7.8 × 10 - 10 m 2 /s, and these are in good agreement with literature values. The novelty of the proposed methodology is in its simplicity and its ability to isolate portions of the pressure-decay data that are affected by experimental fluctuations. This enables the consideration of only that portion of the data that is consistent with the analytical solution.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".