Characterization of static and dynamic geotechnical properties and behaviors of fine coal refuse
Bibliographic record
Abstract
The geotechnical properties, cyclic behavior, and liquefaction resistance of in situ fine coal refuse (FCR) have not been sufficiently investigated. This paper presents the characterization of static and dynamic geotechnical properties of in situ coal slurry samples. Representative coal slurry samples were taken from two coal slurry impoundments in the Appalachian coalfields in the USA. Standard penetration tests (SPTs) were conducted. Index properties, hydraulic conductivity, shear strength, and shear stiffness of the FCR were determined. The geotechnical properties of the representative FCR were found significantly dependent on the location and depth of the samples. However, the FCR samples were classified as soft and low plasticity silty sands to sandy silts. Cyclic direct simple shear (DSS) tests were conducted on representative samples prepared using slurry deposition method to evaluate the liquefaction resistance and cyclic behavior of FCR. The cyclic stress ratio – number of cycles required for liquefaction occurrence (CSR–N) curve for FCR was established. The cyclic resistance of FCR compared well with the empirical correlations for sand-like materials, though the stress–strain behavior and pore-water pressure generation exhibited clay-like behavior. Each cyclic DSS test was followed by a static shearing to assess the post-liquefaction shear strength of the FCR. Significant decrease in shear modulus and dilative behavior were observed after liquefaction.
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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 | 0.001 | 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".