Design and laboratory verification of a physical model of sloping capillary barrier
Bibliographic record
Abstract
A physical model was designed and constructed to study the mechanisms associated with capillary barriers for slope stabilization purposes. Prior to construction of the model, various numerical analyses were conducted to determine the optimum dimensions and appropriate soil types for the materials of the capillary barrier model. This paper is divided into three sections: the first two sections are related to the design of the model and are to obtain the optimum dimensions of the model and to investigate the range of soil properties that are most suitable for experimental studies in the laboratory; and the last section is laboratory verification of the numerical analysis where the numerical simulation results are compared with the experimental data. Based on the numerical simulation results, the physical capillary barrier model was constructed using two different combinations of soils, namely silty sand over gravelly sand and fine sand over gravelly sand. From the comparison of the numerical results and experimental data, it was found that the numerical analysis was able to simulate the experiment on the physical capillary barrier model reasonably well.Key words: physical capillary barrier model, unsaturated water flow, numerical simulation, pore-water pressure, volumetric water content, slope stability, infiltration.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".