Microscopic mechanism analysis of calcareous sand in electrolysis desaturation using <sup>1</sup>H L-F NMR
Bibliographic record
Abstract
Electrolysis desaturation is a novel method to improve the liquefaction resistance of liquefiable foundations. The microscopic mechanism of the horizontal-layered electrolysis desaturation of calcareous sand specimens was revealed using a low-field nuclear magnetic resonance (1H L-F NMR) apparatus. The expansion and recovery of sand pores was detected, and variation pattern of saturation distribution was explored, as well as the generation and migration of gas bubbles. The test results show that the electrolysis mainly discharged free water from the specimen, and the content of bound water or mechanical bound water kept basically unchanged. The rapid generation of the bubbles could lead to the expansion of the sand pores. Within 3 h after stopping electrolysis, the macropores in the calcareous sand essentially returned to the initial state, and the expansion of micropores and mesopores also remained basically stable. The construction method of prolonged low-current electrolysis or short-time multiple electrolysis could be applied for on-site desaturated foundation treatment. The shape and size of the bubbles produced by electrolysis were related to the calcareous sand pores. The migration of gas after stopping electrolysis was mainly in the vertically upward direction, resulting in the fusion of bubbles and the formation of larger bubbles.
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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 | 0.001 | 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 | 0.000 |
| 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".