Influence of the Bituminous Layer on Temperature and Water Infiltration in Railway Structures of the Bretagne–Pays de la Loire High-Speed Line
Bibliographic record
Abstract
Abstract The phenomena of settlement and wear of the ballast under dynamic stresses lead to high frequencies and high maintenance costs on high-speed railway lines. Studies have shown that these settlements are linked to high accelerations produced in the ballast by the passage of high-speed trains (HST). A layer of asphalt concrete (GB) was introduced under the ballast layer on the high-speed line Bretagne-Pays de Loire (BPL HSL). It is intended, among other things, to reduce the amplitude of accelerations produced at the passage of the HST and thus improve the durability of the track. The BPL HSL spans 105 km, with a sublayer of asphalt concrete under the ballast and 77 km with a granular sublayer (UGM). To evaluate the performance of the structures with bituminous sublayer and to compare it with traditional structures with granular sublayer, four track sections have been instrumented during construction. This article presents the different sensors of the instrumentation, as well as the acquisition system installed to collect measurements. The focus, in this study, concerns the temperature, water content, and vertical settlement measurements made on the instrumented sections. Temperature variations recorded during two years on the railway structure with bituminous sublayer were analyzed and compared with those measured on a classical bituminous pavement. Influence of the bituminous layer on water infiltration and track settlements has also been studied.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".