A two-dimensional analytical solution for electro-osmotic consolidation in multi-layered soft soils using vertical electrodes
Bibliographic record
Abstract
The electro-osmosis technique has been proven to be effective in soft ground improvement. Compared to horizontally arranged electrodes, vertically inserted electrodes into the ground offer significant construction advantages, making them the preferred choice for electro-osmotic consolidation. Ground soils often exhibit stratified characteristics; however, the impact of soil stratification on electro-osmotic consolidation using vertical electrodes remains unclear. This study proposes a novel two-dimensional analytical model for electro-osmotic consolidation in multi-layered soils using vertical electrodes to investigate the impact of soil stratification. The separation of variables method is employed to decouple two spatial variables and one temporal variable, resulting in an exact analytical solution. The model is validated against several benchmark cases. Parametric analyses first highlight the versatility of the proposed model, especially in stratified soils with significant variations in hydraulic permeability. Furthermore, analyses of typical three-layered soil systems with a high or low permeability interlayer reveal new insights. Such as a more than twofold increase in negative average excess pore pressure and time to reach 90% average degree of consolidation when the hydraulic permeability of the interlayer is one-tenth that of the surrounding layers. The study provides valuable insights for the design and evaluation of electro-osmotic consolidation in multi-layered soft soils.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".