Knudsen diffusion, gas permeability, and water content in an unconsolidated porous medium
Bibliographic record
Abstract
The Knudsen diffusion coefficient was measured at different levels of water saturation for an unconsolidated porous medium consisting of silt‐sized particles. The Knudsen diffusion coefficient was found to increase from 4.4 × 10−3 cm2/s to 1.0 × 10−1 cm2/s as water saturation decreased from 82% to 54%. A comparison between the experimental Knudsen diffusion coefficients and predicted values of the corresponding effective binary diffusion coefficients indicated that diffusion at high saturations (>64%) were in the transition regime between Knudsen diffusion and molecular diffusion. The results suggest that Knudsen diffusion has significant implications for the prediction of organic vapor transport in partially saturated silts and in less permeable soils. An expression was developed for the influence of water saturation on Knudsen diffusion coefficients, using the Brooks‐Corey capillary pressure saturation relationship. Data from previous studies were also combined with results from this study to develop a correlation between the gas phase permeability and the Knudsen diffusion coefficient for variably saturated porous media. For permeabilities less than 10−10 cm2, the new correlation begins to deviate significantly from an existing correlation for dry porous media.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".