Performance Evaluation of Carrying Capacity of Prestressed Bearers for Railway Turnouts Using Laboratory Experiments in Vietnam
Bibliographic record
Abstract
Previous studies have addressed railway turnouts (switches and crossings), but research on the performance of 1000 mm gauge turnouts is limited. At present, wooden sleeper structures are used at turnouts in Vietnam. However, these structures have many disadvantages in the operation process. This paper evaluates the performance of new prestressed bearer (PSB) for turnouts, designed for the 1000 mm gauge, to overcome the disadvantages of a wooden sleeper. Test samples of PSB were manufactured in the factory, and experiments were conducted in the laboratory according to European Standards to evaluate the PSB carrying capacity. The test results show that the proposed structure meets the carrying capacity under the standard test loads. In addition, the results of the static and fatigue tests of the bearers show a considerable reserve in the cross-section capacity. This means that the existing reserve can be used with a larger locomotive axle, and the bearer design can be optimized by arranging the prestressed strands and changing the bearer cross-section’s geometric dimensions. It is hoped that the proposed bearer design will be a viable alternative for designing railway turnouts.
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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 | 0.001 | 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 | 0.000 |
| 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".