Enhancing the stability of railroad ballast with geogrid reinforcement: an experimental and discrete element modeling study
Bibliographic record
Abstract
Canada possesses an extensive rail network that is mainly supported by ballasted substructures in which a ballast layer lies immediately beneath the rail-tie assembly. The ballast layer performs multiple key functions in a track structure that include supporting the tracks, maintaining their alignment, and transferring train loads to the underlying soil layers. Due to its unbound nature, ballast undergoes substantial deformations when exposed to train loading that disturb the track alignment and compromise the track riding safety. Geogrids have recently emerged as a viable means to stabilize ballast and mitigate its deformations. A geogrid’s ability to reinforce ballast hinges on its interaction with ballast particles, which is a function of parameters such as the geogrid aperture size and location in the ballast layer as well as the subgrade strength that must be investigated. Additionally, geogrids tend to exhibit temperature-dependent mechanical properties. Considering that Canadian railroads tend to be exposed to significant seasonal temperature fluctuations, it is important to determine whether such changes impact the performance of geogrid-reinforced ballast.This thesis begins with an overview of the behavior of ballasted railroad tracks. The use of geogrids to stabilize ballast is then addressed and the various factors influencing the performance of geogrids in ballast are discussed. Chapter 3 then introduces an experimental campaign designed to assess the effect of temperature on the mechanical behavior of a large-aperture biaxial geogrid and a geogrid composite. Single-rib tensile tests are performed in a temperature-controlled environment on specimens of both materials at temperatures ranging from -30⁰C to 40⁰C. The tests reveal that both materials are sensitive to temperature and exhibit increasingly brittle responses as the temperature decreases below 20⁰C and ductile behaviors at elevated temperatures.In Chapter 4, a series of large-scale ballast box tests is conducted to investigate the effect of the geogrid placement depth and subgrade strength on the cyclic loading response of geogrid-reinforced ballast. In these experiments, 300mm-thick ballast layers are constructed over artificial subgrades with California Bearing Ratios of 25, 13, and 5 and are reinforced with a single geogrid layer located at depths of 150mm, 200mm, and 250mm beneath the tie. The results indicate that the geogrid placement depth wields a negligible impact on the response of geogrid-reinforced ballast supported by a strong subgrade. However, for softer subgrades, shallow placement depths enhance a geogrid’s ability to reinforce ballast, leading to smaller tie settlement and greater tie support stiffness.Finally, building on the observations drawn in Chapter 4, three-dimensional discrete element simulations of the ballast box tests are performed to delve into the micromechanical features of the ballast-geogrid interaction mechanism. The geogrid placement depth is first varied from 50mm to 250mm below the tie and the simulations reveal that geogrids located within the ballast layer’s upper 150mm are more effective at stabilizing ballast by virtue of being located within the volume of aggregate that displaces the most in response to cyclic loading. The geogrid aperture size ratio (A/D) is then varied from 1.09 to 2.91 while the geogrid stiffness is assigned values ranging from 9.54 to 18kN/m corresponding to the geogrid’s tensile strength at 2% strain at temperatures ranging from 40⁰C to -30⁰C as discussed in Chapter 3. An A/D ≥ 1.45 is required for a stable geogrid-ballast interlock to form, as lower ratios imply the geogrid aperture size is too small to allow ballast interlocking, leading to the formation of a preferential slippage plane along the geogrid’s interface. On the other hand, the range of stiffnesses considered in the simulations appears to wield a marginal effect on the behavior of geogrid-reinforced ballast
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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) | 0.000 | 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 | 0.000 |
| 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".