Modeling Gas Formation and Mineral Precipitation in a Granular Iron Column
Bibliographic record
Abstract
In granular iron permeable reactive barriers (PRBs), hydrogen gas formation, entrapment and release of gas bubbles, and secondary mineral precipitation have been known to affect the permeability and reactivity. The multicomponent reactive transport model MIN3P was enhanced to couple gas formation and release, secondary mineral precipitation, and the effects of these processes on hydraulic properties and iron reactivity. The enhanced model was applied to a granular iron column, which was studied for the treatment of trichloroethene (TCE) in the presence of dissolved CaCO(3). The simulation reasonably reproduced trends in gas formation, secondary mineral precipitation, permeability changes, and reactivity changes observed over time. The simulation showed that the accumulation of secondary minerals reduced the reactivity of the granular iron over time, which in turn decreased the rate of mineral accumulation, and also resulted in a gradual decrease in gas formation over time. This study provides a quantitative assessment of the evolving nature of geochemistry and permeability, resulting from coupled processes of gas formation and mineral precipitation, which leads to a better understanding of the processes controlling the granular iron reactivity, and represents an improved method for incorporating these factors into the design of granular iron PRBs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".