Effect of relative density and biocementation on cyclic response of calcareous sand
Bibliographic record
Abstract
Microbial-induced calcium carbonate precipitation (MICP) represents a promising approach to improve the geotechnical engineering properties of soils through the precipitation of calcium carbonate (CaCO3) at soil particle contacts and soil particle surfaces. An extensive experimental study was undertaken to investigate the influence of initial relative density on the efficiency of the biocementation process, the reduction of liquefaction susceptibility, and the cyclic response in biocemented calcareous soils. For this purpose, stress-controlled undrained cyclic triaxial shear (CTS) tests were carried out on untreated and MICP-treated calcareous sand specimens for different initial relative densities and magnitudes of biocementation. Improvement in the cyclic response was quantified and compared in terms of excess pore pressure generation, evolution of axial strains, and the number of cycles to liquefaction. The cyclic experiments show that MICP treatment can change the liquefaction failure mechanism from flow failure to cyclic mobility and can significantly change the excess pore pressure generation response of initially loose specimens. Scanning electron microscope (SEM) images indicate the CaCO3 crystals alter the characteristics of the sand particles and confirm the physical change in soil fabric that impacts the dynamic behavior and liquefaction resistance of MICP-treated specimens. Furthermore, the effect of biocementation was contrasted against the effect of relative density alone, and MICP treatment was shown to exhibit greater efficiency in improving the cyclic resistance than densification.
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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 | 0.000 | 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".