Use of tire shred-sand mixtures as backfill material for mechanically stabilized earth retaining walls
Bibliographic record
Abstract
Enormous quantities of waste tires are generated annually in all countries around the world. Efforts have been made to find applications for scrap tires in various industries. As a result, over the last few years there has been increased use of scrap tires in a variety of applications. One of the applications of scrap tires in civil engineering is in their use as a lightweight backfill material for mechanically stabilized earth (MSE) walls, where the shredded tires are mixed with sand. This has been shown to have several advantages, including lower vertical stress on weak foundation soils, lower horizontal pressures on the wall and good drainage properties. For tire shred-sand mixtures to be used as backfill material for MSE walls, their geotechnical properties need to be estimated. The pullout resistance of reinforcements embedded in tire shred-sand mixtures and the shear strength characteristics of the mixtures need to be determined. Conventional testing equipment proved to be unsuitable due to their small sizes relative to the size of the tire shreds. In this study, large-scale laboratory pullout tests were performed on reinforcement ladders embedded in mixtures prepared with tire shreds (size: 50-100 mm in length) and Ottawa sand. The pullout tests were performed at various mixing ratios (0:100, 20:80, 25:75, 35:75 and 45:55 by weight of tire shreds to sand) and confining pressures (40, 65 and 90 kPa). Large-scale direct shear tests were performed on tire shred-sand mixtures at mixing ratios of 20:80 and 35:65 by weight of tire shreds to sand. The results from the pullout tests showed that the pullout capacity of reinforcement ladders was higher in tire shred-sand mixtures than in pure sand. This can be attributed to the interlocking of tire shreds in the grids of the reinforcement ladder, thus providing higher passive resistance against pullout compared to that of pure sand. The pullout capacity increased with increases in the confining pressure at all mixing ratios. At a given confining pressure, increases in the tire shred content in the mixture typically resulted in higher pullout resistance. According to the results from the large-scale direct shear tests, critical-state friction angles of 30.1° and 32.0° and peak friction angles of 31.0° and 32° were obtained for tire shred-sand mixtures prepared at mixing ratios equal to 20:80 and 35:65 by weight of tire shreds to sand, respectively. When the results of the large-scale direct shear tests were plotted with a nonzero cohesive intercept, c-phi fitting parameters of 14.5 kPa and 27.1° and 10.3 kPa and 29.6° were obtained for tire shred-sand mixtures prepared at mixing ratios of 20:80 and 35:65 by weight of tire shreds to sand, respectively.
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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) | 0.001 | 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 | 0.000 |
| 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".