Effect of Sample Size on TDA Shear Strength Parameters in Direct Shear Tests
Bibliographic record
Abstract
Tire-derived aggregate (TDA), a relatively new construction material, has been gaining acceptance as a backfill material for embankments, trenches, and earth-retaining structures because of its lightweight and excellent geotechnical properties. Type A TDA has a basic geometric shape, with particles approximately 12 to 100 mm in size. As a result of the simplicity and accuracy of the direct shear test, most laboratories choose this test in preference to more complex tests. However, TDA requires large-scale direct shear apparatus because of the consistently large size of its particles, and few facilities own this type of apparatus. Depending on the shear box dimensions, the aspect ratio of the particle size to the box dimensions may lead to variations in the shear strength results of the sample being evaluated. This research focuses on studying the effect of TDA sample size on the shear strength results of direct shear tests by using five different shear box sizes. The findings show that the angle of internal friction increases slightly as the dimensions of the shear box decrease. It was found that the maximum variation in the angle of internal friction and the cohesion results of the different shear boxes was only 1.9° and 2.4 kPa, respectively. These differences should be taken into consideration when TDA shear test results are used in the geotechnical design. It is recommended that a shear box with an aspect ratio (W/D max ) greater than or equal to 4 should be used when evaluating the shear strength parameters of TDA.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".