Geotechnical Characterization of Compacted Bauxite Residue for Use in Levees
Bibliographic record
Abstract
This paper describes the results from a laboratory test program developed to characterize and evaluate the geotechnical properties of compacted bauxite residue, a byproduct from the production of alumina. Demand for suitable fill materials to construct flood-protection levees, particularly along the U.S. Gulf Coast, prompted this study to determine if bauxite residue could be a feasible solution. The laboratory test program consisted of characterization tests and performance tests including shear strength, hydraulic conductivity, erosion resistance and compressibility. Samples of both untreated bauxite residue and alkalinity-adjusted bauxite residue were tested. The results provide several conclusions. The characterization tests show that bauxite residue behaves like a fine-grained, plastic soil. Oven-drying the material before testing affects its geotechnical behavior and provides impractical results. In a compacted state, bauxite residue has a low hydraulic conductivity that is resistant to internal erosion and suitable for the core of a flood-protection levee. Compacted bauxite residue has a shear strength that is greater than fine-grained soils typically used in levees, potentially reducing the necessary footprint and volume required for a levee constructed with this material. The high alkalinity of untreated bauxite residue makes it necessary for neutralization or encapsulation to minimize its impact on the environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".