Conceptual Models and Simulations for Biological Clogging in Unsaturated Soils
Bibliographic record
Abstract
Biological clogging in unsaturated soils is an important concern in the design of biofilters that are used to treat wastewater in rural areas. Several conceptual models have been developed to simulate biological clogging in saturated flow systems but limited research has been performed to develop similar conceptual models in unsaturated soils. This study developed three conceptual models for biological clogging in unsaturated soils. The model formulations varied from microscale to macroscale and from analytically derived to empirical equations. They were all formulated based on the approaches proposed by Burdine and Mualem to estimate the relative permeability based on the effective water saturation and the soil moisture curve. A one‐dimensional unsaturated flow and transport code was developed, which incorporates Monod kinetics to simulate the biodegradation of an organic substrate. The three conceptual models that were developed relate the relative permeability to the microbial growth term in the unsaturated flow equation. The models were implemented in a numerical model to illustrate the impact of microbial growth on the biological clogging of unsaturated soils. Also the effect of continuous loading versus pulse loading was simulated to illustrate the difference between the loading scenarios on the clogging process within biofilters.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".