Field and Laboratory Evaluation of a Diffusive Emitter for Semipassive Release of PCE to an Aquifer
Bibliographic record
Abstract
Abstract In controlled field experiments or model aquifers, it is sometimes desirable to introduce solutes below the water table without perturbing the flow system. Diffusive emitters offer a means of achieving that goal. In this study, two laboratory experiments were conducted to evaluate nylon tubing as a diffusive emitter for tetrachloroethene (PCE). The initial approach was to pump a saturated aqueous PCE solution through a piece of nylon tubing immersed in a flow‐through contactor vessel. Millipore water was pumped through the contactor vessel at a constant rate. Due to PCE diffusion through the nylon, a steady‐state concentration in the contactor vessel eventually developed. The process was well described by a computer model that accounted for retarded diffusion through the nylon. In a second experiment, pieces of nylon tubing were exposed to a relatively low concentration of PCE in water for 10 days in gently rotated hypovials. With the aid of a second diffusion model, the bulk diffusion coefficient (lumped with the retardation factor) was obtained from the concentration history of the solution. With the different experimental conditions taken into account, there was reasonably good agreement between the bulk diffusion coefficients in the two experiments (a factor of 3.5 difference). The results were used in the field design of a semipassive release system. Evaluation of this system showed a lower than expected steady‐state concentration of PCE inside the releasing wells. The difference is likely due to lower temperature, variable PCE concentrations in the nylon tubing, and nonideal mixing in the wells. The work has shown that laboratory derived diffusion coefficients for polymeric materials are likely to be larger than, but within an order of magnitude of, the effective diffusion coefficients exhibited by emitters in the field. Nevertheless, with temperature corrections taken into account and proper well development, these values could be used to design emitters that would suit most practical applications.
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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 | 0.001 | 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 | 0.000 | 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) | 0.001 | 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".