Effects of electrokinetic phenomena on the load-bearing capacity of different steel and concrete piles: a small-scale experimental study
Bibliographic record
Abstract
To date, the electrokinetic (EK) method has only been used to increase the bearing capacity of steel piles. This study analysed the impact of EK on the bearing capacity of reinforced cement concrete piles (RCCP), reinforced lime-cement concrete piles (RLCCP), and steel piles located in kaolin clay. The performance of four different cathodes was also evaluated, and the iron electrode was found to be the most effective cathode for use in the EK process. Unlike RLCCP, the bearing capacity of 7 day cured RCCP with 5 day EK decreased due to corrosion in the pile body. However, the addition of lime to RCCP significantly increased the pile bearing capacity by 57.8% with 8 day EK and prevented damage and corrosion in the pile body. It is concluded that EK can effectively increase the bearing capacity of both metallic and even concrete piles.
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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) | 0.001 | 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 | 0.001 |
| 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".