Numerical Examination of the Factors Controlling DNAPL Migration Through a Single Fracture
Bibliographic record
Abstract
The migration of five dense nonaqueous phase liquids (DNAPLs) through a single fracture in a clay aquitard was numerically simulated with the use of a compositional simulator. The effects of fracture aperture, fracture dip, matrix porosity, and matrix organic carbon content on the migration of chlorobenzene, 1,2-dichloroethylene, trichloroethylene, tetra-chloroethylene, and 1,2-dibromoethane were examined. Boundary conditions were chosen such that DNAPL entry into the system was allowed to vary according to the stresses applied. The aperture is the most important factor of those studied controlling the migration rate of DNAPL through a single fracture embedded in a clay matrix. Loss of mass to the matrix through diffusion does not significantly retard the migration rate of the DNAPL, particularly in larger aperture fractures (e.g., 50 microm). With time, the ratio of diffusive loss to the matrix to DNAPL flux into the fracture approaches an asymptotic value lower than unity. The implication is that matrix diffusion cannot arrest the migration of DNAPL in a single fracture. The complex relationships between density, viscosity, and solubility that, to some extent, govern the migration of DNAPL through these systems prevent accurate predictions without the use of numerical models. The contamination potential of the migrating DNAPL is significantly increased through the transfer of mass to the matrix. The occurrence of opposite concentration gradients within the matrix can cause dissolved phase contamination to exist in the system for more than 1000 years after the DNAPL has been completely removed from the fracture.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".