The effect of recycled rubber energy-absorbing grids on the cyclic shear response of ballast
Bibliographic record
Abstract
Ballasted railway tracks are increasingly subjected to higher axle loads and speeds, accelerating ballast degradation, settlement, and maintenance needs. Traditional solutions like under-ballast mats (UBMs) and polymer geogrids provide either energy absorption or lateral confinement—but not both. To address this, a novel reinforcement system called recycled rubber energy absorbing grids (REAGs) is introduced, made from discarded mining conveyor belts. REAG combines the damping capacity of UBMs with the interlocking effect of geogrids to enhance ballast performance under cyclic loading. This study presents large-scale cyclic direct shear tests to assess the dynamic interface behaviour of ballast reinforced with REAG, compared to a conventional polymer geogrid. Tests were conducted under varying cyclic normal stresses ( σ n , max = 25, 50, 100 kPa) and frequencies ( f = 5, 10 Hz) to replicate typical train loading. Key parameters examined include interface shear strength, shear stiffness, damping ratio, vertical displacement, and ballast breakage. Results show that REAG significantly enhances interface shear performance, reduces deformation, and minimises ballast breakage more effectively than traditional geogrids. This study highlights REAG’s potential as a sustainable and effective solution for extending the service life of ballasted railway tracks through combined energy dissipation and mechanical confinement.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".