Elastic Modulus of Geogrid-Reinforced Sand Using Plate Load Tests
Bibliographic record
Abstract
Abstract An experimental study was conducted to evaluate the elastic modulus of sand reinforced with polymeric geogrids. A total of nine plate load tests were performed in the laboratory using a 1.52 m × 1.52 m × 1.37 m (length × width × depth) test box, and a 0.3 m square test plate. The measured test data were used to evaluate a modulus constant (E1), rather than the bearing capacity, as traditionally presented in literature. The modulus constant was estimated based on two deformation levels of 9.2 mm and 4.6 mm. These deformation levels, defined as δ1 and δ0.5, correspond to normalized settlement ratios (δ/B) of 1.5 and 3.0%, respectively, where B = width of the test plate. In general, a stiffer load-settlement response was measured when the geogrid reinforcement was included. Using SR1 geogrids with sand, the modulus constant (E1) decreased as a function of increasing u/B ratio (u = distance from plate to Eop reinforcement layer). In comparison, results indicated the presence of a critical u/B ratio when the SR2 geogrids were used. In this study, this particular ratio was estimated to be 0.65. Values of E1 from large scale model testing by Adams and Collin (1997) correlated well with E1 values evaluated from this testing program.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".