Effect of Initial Conditions on the Interpretation of Soil-Water Characteristic Curves (SWCCs) in Geotechnical Engineering
Bibliographic record
Abstract
The test procedure for measuring the soil-water characteristic curve, SWCC, have been largely established within the soil physics discipline over a period of several decades. More recently, these test procedures have been incorporated into geotechnical engineering practice. While there are benefits associated with utilizing past experience, further refinement of the analytical procedures used in soil physics are required when estimating unsaturated soil property functions. The primary assumption that has historically been made is that insignificant volume change occurs as soil suction is increased during the drying process. This assumption may be satisfactory for certain soil types and conditions, but in general, the effects of volume change are significant for many soils and must be taken into consideration when estimating USPFs. The shrinkage curve (SC) of a soil can be effectively used to take volume changes upon drying into consideration. The shrinkage curve can readily be measured but there are also a number of means whereby the curve can be estimated with sufficient accuracy. This paper outlines the steps involved in independently assessing the effects of volume change and desaturation on the calculation of unsaturated soil property functions. The shrinkage curve is used to separate the various volume-mass SWCCs required when dealing with various unsaturated soil mechanics problems. The proposed analytical procedure is described for estimation of hydraulic properties for low to high compressibility 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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| 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".