Hydraulic Displacement of Dense Nonaqueous Phase Liquids for Source Zone Stabilization
Bibliographic record
Abstract
Hydraulic displacement is a mass removal technology suitable for stabilization of a dense, nonaqueous phase liquid (DNAPL) source zone, where stabilization is defined as reducing DNAPL saturations and reducing the risk of future pool mobilization. High resolution three-dimensional multiphase flow simulations incorporating a spatially correlated, heterogeneous porous medium illustrate that hydraulic displacement results in an increase in the amount of residual DNAPL present, which in turn results in increased solute concentrations in groundwater, an increase in the rate of DNAPL dissolution, and an increase in the solute mass flux. A higher percentage of DNAPL recovery is associated with higher initial DNAPL release volumes, lower density DNAPLs, more heterogeneous porous media, and increased drawdown of groundwater at extraction wells. The fact that higher rates of recovery are associated with more heterogeneous porous media stems from the fact that larger contrasts in permeability provide for a higher proportion of capillary barriers upon which DNAPL pooling and lateral migration can occur. Across all scenarios evaluated in this study, the ganglia-to-pool (GTP) ratio generally increased from approximately 0.1 to between approximately 0.3 and 0.7 depending on the type of DNAPL, the degree of heterogeneity, and the imposed hydraulic gradient. The volume of DNAPL recovered as a result of implementing hydraulic displacement ranged from between 9.4% and 45.2% of the initial release volume, with the largest percentage recovery associated with 1,1,1 trichloroethane, the least dense of the three DNAPLs considered.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".