Laboratory investigation of LNAPL migration in unsaturated porous media
Bibliographic record
Abstract
Soil and groundwater contamination with non aqueous phase liquids (NAPLs) are often found at contaminated sites and it lead sophisticated procedure for remediation. This research experimentally investigates the effects of groundwater movement on the migration of LNAPL in the subsurface. Diesel was selected as LNAPL and it can be classified as a light non-aqueous phase liquid (LNAPL) because of its lower density than water. Ottawa#3820 sand and Ottawa#3 sand were used as porous media. The Simplified Image Analysis Method (SIAM) (Flores, 2010) is used as a non-intrusive and non-destructive technique to measure temporal and spatial distribution of fluid saturations in a whole domain. Linear relationships between average optical density (AOD) and degree of water saturation (S[subscript w]) and Degree of diesel saturation (S[subscript o]) for Ottawa#3820 sand and Ottawa#3821 sand were established as required by SIAM. One-dimensional column (3.5 cm x 3.5 cm x 110 cm transparent acrylics column) is used to study the effects of water table fluctuation and Two-dimensional tank (3.5 cm x 50 cm x 60 cm transparent acrylic tank) is used to study totally effects of groundwater level fluctuation and horizontal groundwater flow. 8 one-dimensional column tests and 12 two-dimensional tank tests in homogeneous and heterogeneous porous media were conducted. The results show that the water table fluctuation significantly affects the LNAPL distribution in the ground to the full range of the water saturated zone and vadose zone. A higher horizontal groundwater flow rate renders the larger diesel-contaminated area comparing with lower flow rate also results in a larger area of diesel contamination.
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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 | 0.000 | 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".