One-dimensional large strain electroosmotic consolidation of ultra-soft geomaterials
Bibliographic record
Abstract
Electrokinetic (EK) consolidation has been proven to effectively consolidate ultra-soft geomaterials, such as coal washeries, mine tailings, oil sands tailings and so on. The conventional consolidation model based on the small strain theory encountered difficulties with these geomaterials due to continuous changes in material properties during consolidation. This research developed a one-dimensional large strain EK (LSEK-1D) consolidation model for ultra-soft geomaterials. The model is validated using experimental laboratory results regarding settlements and times on mature fine oil sand tailings (MFT), a major environmental challenge for the oil industry in Northern Alberta, Canada. Moreover, the effects of initial sample heights and applied current densities on consolidation times are evaluated. The experimental data on consolidation times of MFT is consistent with the LSEK-1D model. The LSEK-1D model was used to find the scale effect of drainage path on the EK consolidation behaviour of MFT. The model can also be used for other ultra-soft geomaterials and to facilitate the geotechnical engineering design for EK application.
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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 | 0.001 | 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".