Characterizing cyclic and static moduli and strength of compacted pavement subgrade soils considering moisture variation
Bibliographic record
Abstract
Compacted soils are widely used as the subgrade layer for pavements. Knowledge of the mechanical properties of subgrade soils under cyclic and static loading conditions and their variation under the influence of environmental factors is required for the rational design of pavements based on mechanistic methods. This paper presents an experimental investigation of the cyclic and static moduli and the strength properties of seven different compacted Canadian subgrade soils considering the variation in the post-compaction moisture content. Cyclic triaxial tests were performed to reliably determine the resilient modulus ( M R ). Unconfined compression tests, which allow an unloading-reloading loop at 1% strain, were performed to determine the deviator stress ( S u 1% ) at 1% strain, the reloading elastic modulus ( E 1% ) at 1% strain and the unconfined compressive strength ( q u ) at failure. The physical properties, the chemical and mineralogical compositions, and the soil-water characteristics of these soils were also determined. Relationships were developed to predict the M R from the S u 1% , E 1% , q u and soil physical properties for the investigated subgrade soils because the experimental determination of M R is both expensive and time-consuming. The studies presented in this paper provide useful information and approaches that can be used to promote the implementation of mechanistic pavement design methods using simple techniques.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".