Resonant Column Testing Procedure for Microbial-Induced Carbonate-Precipitated Sands
Bibliographic record
Abstract
ABSTRACT One of the fundamental inputs to site response analysis is the characterization of the dynamic properties of the soil, namely the shear modulus and material damping ratio. Because of soil’s nonlinear behavior, these properties change with induced shear strains, and modulus reduction and damping (MRD) curves have been proposed to capture that cyclic shear strain dependency. Microbial-induced carbonate precipitation (MICP) is a natural cementation process that induces the precipitation of calcium carbonate, bonding soil particles together. Laboratory experiments have demonstrated that MICP can improve the mechanical behavior of soils and mitigate their liquefaction potential. However, MRD curves have not been developed for MICP-treated soils, which hinders further evaluations of their suitability as a ground improvement technique for geotechnical earthquake engineering applications. To the best of our knowledge, this paper provides the first empirical study measuring the shear strain–dependent dynamic properties of MICP-treated sands for different cementation levels (i.e., lightly to heavily cemented). Outcomes from this work include empirical models of the maximum shear modulus and minimum shear strain damping ratio of MICP-treated clean sands and the corresponding mean MRD curves. The experimental program includes MICP-treated specimens of Ottawa 20-30 sand tested with a resonant column (RC) device incorporating a modified RC porous disk that (1) minimizes the disturbance between treatment and installation of MICP-treated samples prior to being tested in the RC device, (2) prevents slippage between the specimen and the modified RC porous disk during RC shearing, and (3) enables repeatability of the MICP-treated sample preparation. We find that the level of cementation influences the MRD curves of MICP-treated sands. Linear elastic and volumetric shear strain thresholds for MICP-treated sands are smaller than those for untreated sands, whereas the initial shear modulus for treated soils is larger than its counterpart for untreated sands.
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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 | 0.000 |
| 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) | 0.002 | 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".