Development of a model to predict the water retention curve using basic geotechnical properties
Bibliographic record
Abstract
RÉSUMÉ: La courbe de rétention d'eau (CRE) est devenue une fonction clé pour définir le comportement non saturé des sols et d'autres matériaux meubles. Dans beaucoup de cas, il peut être très utile d'avoir une évaluation de la CRE dans les pr emières phases d'un projet, lorsque peu ou pas de résultats d'essais sont disponibles. Des modèles prédictifs, basés sur les propriétés géotechniques de base, peuvent aussi être utilisés pour évaluer comment le changement des paramètres (en termes de porosité ou de granulométrie) affecte la CRE. Dans cet article, les auteurs présentent un ensemble d'équations développées pour prédire la relation entre la teneur en eau volumique θ (et le degré de saturation S r correspondant) et la succion ψ . Le modèle proposé pour la prédiction de la CRE est une version modifiée du modèle de Kovács (1981), qui fait une distinction entre la rétention d'eau due aux forces capillaires et celle par adhésion. Ce jeu d'équations est donné avec des relations complémentaires développées pour des applications spécifiques sur des matériaux granulaires et sur des sols (argileux) plastiques/c ohérents. Il est montré que le modèle constitue un moyen simple et pratique pour estimer la courbe de rétention d'eau à partir des propriétés géotechniques de base. Une discussion suit sur les capacités et les limitations du modèle. ABSTRACT: The water retention curve (WRC) has become a key material function to define the unsaturated behavior of soils and of other particulate media. In many instances, it can be very useful to have an estimate of the WRC early in a project, when little or no test results are available. Predictive models, based on easy to obtain geotechnical prope rties, can also be employed to evaluate how changing parameters (e.g. porosity or grain size) affect the WRC. In this paper, the authors present a general set of equations developed for predicting the relationship between volumetric water content θ (and the corresponding degree of saturation S r ) and suction ψ . The proposed WRC model is a modified version of the Kovács (1981) model, which makes a distinction between water retention due to capillary forces and retention by adhesion. The complete set of equations is given together with complementary relationships developed for specific applications on granular materials and on plastic/cohesive (clayey) soils. It is shown that the model provides a simple and practical means to estimate the water retention curve from basic properties. A discussion follows on the capabilities and limitations of the model.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".