Numerical simulations of a light nonaqueous phase liquid (LNAPL) movement in variably saturated soils with capillary hysteresis
Bibliographic record
Abstract
The fate and transport of pollutants in the subsurface is usually predicted using numerical simulations. Comparisons of the simulation results with experimental data are required to validate the numerical codes. In this paper, the nonaqueous phase liquid (NAPL) simulator code was used to numerically simulate two centrifugal light nonaqueous phase liquid (LNAPL) transport experiments. The numerical predictions were compared with the centrifugal test results and the impact of capillary hysteresis was evaluated. It was concluded that the simulation with the nonhysteretic model slightly underestimated the LNAPL volume retained in the vadose zone, and the average error of the predicted LNAPL saturation in the vadose zone and along the plume centerline was approximately 5% to 10%. The application of capillary hysteresis for the numerical simulation of the second centrifuge test has eliminated this error. In addition, accounting for hysteresis in the numerical simulation of the second centrifuge test has considerably improved the predicted results with respect to the size of the lens-shaped plume within the capillary fringe. However, there were inconsistencies between the numerical and experimental results, especially with respect to the time for the LNAPL to reach the groundwater level. This was found to be due to overestimation of the simulated downward infiltration of the LNAPL in the capillary fringe. It was found that the pore-connectivity parameter with a value of 0.66 for the relative permeability–saturation model produced the best comparison with experimental results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".