Modelling resilient modulus seasonal variation of silty sand subgrade soils with matric suction control
Bibliographic record
Abstract
The resilient modulus of unbound materials is an important parameter in the mechanistic design of pavements. Although unbound layers are frequently in a partially saturated state, a total stress approach is conventionally used in modeling the material behaviour, and therefore pore pressure effects are not considered. In fine-grained unbound materials, the saturation state can affect their mechanical behaviour due to pore pressure effects. In this study a modified test procedure and a predictive resilient modulus model that takes into account the subgrade soil matric suction as a stress state variable is presented. Two different silty sand subgrade materials were tested in unsaturated conditions using a series of repeated load triaxial tests under controlled pore suction conditions to study its influence on the resilient modulus. The test data were further used to obtain the resilient modulus model regression parameters that account for moisture content variations through the matric suction parameter. Generally, the prediction model could effectively capture the resilient modulus behaviour of the subgrades with respect to changes in the normal stress state and the matric suction. Given the completeness of this method, this prediction model is recommended as an improved approach in capturing the moisture content effects on the material stiffness properties.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".