In situ desaturation tests by electrolysis for liquefaction mitigation
Bibliographic record
Abstract
Electrolytic desaturation is a potential method for improving the liquefaction resistance of liquefiable foundations by reducing the soil saturation. In this study, in situ desaturation tests were performed to investigate the resistivity of soil at different depth and water level of the foundation under different currents. The test results show that at constant currents of 1, 2, and 3 A (ampere, unit of the direct current), the saturation of the treated foundation reached 87%, 83%, and 80%, respectively. During the electrolysis process, the generated gas migrates vertically and horizontally under the influence of buoyancy and gas pressure. In the end of electrolysis, the gas inside the sand foundation basically migrates vertically only. The higher current intensity employed for electrolysis will affect the uniformity and stability of the gas. At constant currents of 1, 2, and 3 A, the difference between the maximum and minimum degree of saturation in the treated foundation was 14%, 18%, and 19%, respectively; and after electrolysis had been halted for 144 h, the saturation in the treated foundation was 90%, 85%, and 87%, respectively. The electricity consumption analysis indicates that the desaturation method has excellent economic benefits in the treatment of saturated sand foundations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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".