Gas-facilitated NAPL transport during bench-scale thermal conduction heating experiments
Bibliographic record
Abstract
Thermal conduction heating (TCH) is a subsurface remediation technology used for the removal of volatile and semi-volatile non-aqueous phase liquids (NAPLs). Gas produced during TCH facilitates NAPL removal and above ground treatment but can also redistribute NAPL within and outside of source zones. Bench-scale TCH experiments were conducted to investigate the redistribution of trichloroethene (TCE) and creosote in both coarse and medium sand. In the coarse sand, both NAPLs were transported upwards through the gas zone via double displacement and spreading mechanisms, facilitated by discontinuous gas flow. With sustained heating, TCE was removed via co-boiling, but only the higher volatility components in the transported creosote were depleted. In the medium sand, a continuous gas channel expanded away from the heater, resulting in limited TCE redistribution due to co-boiling, but substantial upwards and lateral transport of creosote away from the gas zone. This work highlights the potential risk for NAPL transport away from the heated region during TCH, which may be mitigated through accurate site investigation and the installation of perimeter heaters. This work also emphasizes the need to heat the entire treatment zone to the target temperature to promote removal of any displaced NAPL.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".