Laboratory Characterization of Saskatoon Tire Derived Aggregate (TDA)
Bibliographic record
Abstract
Tire derived aggregate (TDA) is composed of shreds of scrap tires varying in size. Tire derived aggregate has been used as a replacement for crushed rock aggregate in various Civil Engineering applications including embankments, pavement structures, fill, and leachate collection systems. Using shredded tire in lieu of conventional rock aggregates offers environmental and economic benefits. Tire derived aggregate has good thermal insulator characteristics and can therefore be used to reduce frost penetration. It also promotes good drainage, is lightweight, compressible, and has no harmful leachates. Using tire derived aggregate offers these unique properties at a reduced cost compared to conventional aggregates. Using tire derived aggregate also reduces pressures on aggregate pits and landfills, where the tires would otherwise be discarded. This study examined the physical characteristics of tire derived aggregate and sand mixes in the laboratory for road sub-structure drainage applications. Non-linear permeability and stiffness analysis of 100% TDA, 100% sand, and various TDA-sand blends was performed. It was found that a 70/30 blend of clean sand and tire derived aggregate provides adequate structural capacity while still maintaining good drainage characteristics. The material properties of these mixes were used as inputs in a three dimensional finite element model to perform simulations and generate road primary response outputs. Based on the analysis performed, it was determined that tire derived aggregate systems exhibit highly non-linear material constitutive behaviour in terms of permeability as well as mechanical primary response with respect to stress state. It was also determined that when designed properly, tire derived aggregate is a technically and economically sound alternative for road substructure drainage layers.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".