Effective constitutive properties for dense nonaqueous phase liquid (DNAPL) migration in large fracture networks: A computational study
Bibliographic record
Abstract
Large‐scale capillary pressure [ ] and effective permeability‐saturation [knw ] constitutive relationships for an incompressible, two‐phase system have been developed for a two‐dimensional, nonorthogonal fracture network utilizing numerical simulation. The simulations account for capillary, viscous, and gravity effects consistent with the Darcian approach adopted for this study, and were performed within the scale of the REV of the system which was consistent for both single and multiphase flow behavior. The large‐scale relationship for steady state flow conditions was found to be sensitive to the mean and the variance of the underlying aperture distribution as well as the nonwetting phase density. The overall effects of varying the aperture statistics on the relationships were found to be analogous to porous media, with an increased mean aperture leading to lower capillary pressures and an increased aperture variance leading to steeper curves. The large‐scale knw curves representative of flow in the vertical direction followed the general form of the underlying local‐scale Brooks‐Corey constitutive relationship and were relatively insensitive to a change in variance of the aperture distribution. The large‐scale knw curves representing flow in the horizontal direction due to an imposed gradient in the vertical direction, however, are significantly different than the underlying local‐scale relationships, showing maximum values at intermediate saturations. The ratio of vertical to horizontal effective permeability is saturation dependent.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".