Laboratory Tests on Mitigation of Soil Liquefaction Using Microbial Induced Desaturation and Precipitation
Bibliographic record
Abstract
Abstract Microbial induced desaturation and precipitation (MIDP) is an emerging bio-mediated ground improvement method in which nitrate-reducing bacteria in the soil are stimulated to produce biogas and biominerals. In this study, the potential of MIDP for mitigating soil liquefaction was evaluated using a modified triaxial setup. Modifications to the triaxial test setup allowed the change in the degree of saturation during treatment and the mechanical response to cyclic and monotonic loading to be measured. An experimental procedure was developed to simulate the in situ treatment process of a sand layer underneath an embankment along the Fraser River in Richmond, British Columbia, Canada, which was susceptible to liquefaction. Denitrifying microbes were enriched from locally collected soil. Reconstituted samples were treated with a single MIDP treatment cycle under similar stress conditions as encountered in the field. Triaxial consolidated undrained cyclic and monotonic tests were performed to investigate the mechanical response of the treated soil. Results showed that a single MIDP treatment cycle reduced the degree of saturation to 80 % and produced an average calcium carbonate content of 0.086 %, and significantly increased the cyclic shear resistance.
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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 | 0.000 |
| 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) | 0.001 | 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".