Investigation into Some Design Aspects of Ballasted Railway TrackFoundations using Numerical Modelling
Bibliographic record
Abstract
Railways have become the most popular means of public transportation in many countries around the world.Therefore, an investigation into the impact of design parameters affecting the overall behaviour of railway track foundations under train dynamic loading is necessary for optimum and reliable design.Railway track foundations consist of a graded layer of granular media of ballast and subballast, which is laid on a naturally deposited subgrade soil.Most available methods for design of ballasted railway track foundations assume linear elastic behaviour for track geomaterials.However, the resilient behaviour of track geomaterials, especially the ballast layer, is mostly non-linear and may incur plasticity, depending on the level of applied stress.In this paper, a sophisticated three-dimensional finite element modelling is developed to investigate the track response subjected to train moving loads, by considering actual characteristics of track geomaterials including non-linearity and plasticity.The results are compared with the simpler elastic modelling response, and the practical implications are discussed.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".