A preliminary investigation of the potential benefits of using the ASTRA Bridge for short-span bridge deck refurbishment projects in Switzerland
Bibliographic record
Abstract
How bridge refurbishment projects are performed requires a trade-off between the speed and cost of the project and the amount of traffic disturbances during the project. A possible way to help reach a better balance between these two extremes is the ASTRA Bridge developed in Switzerland. The ASTRA Bridge is a 236-meter long steel ramp system on wheels, which is placed on top of the bridge deck undergoing refurbishment to enable vehicles to continue to pass over the bridge while construction work progresses underneath. This study illustrates new refurbishment processes by using the ASTRA Bridge and presents the first quantitative analysis of the effects of using the ASTRA Bridge on the time, costs and traffic disturbances associated with bridge refurbishment. The bridge investigated is a short-span (50 m long) highway bridge requiring refurbishment of its superstructure. The analysis indicates that the use of the ASTRA Bridge resulted in reductions in duration and costs (14% and 3% for the example), and a substantial reduction in user costs (51% for the example). Although more analysis is required for different types of refurbishment projects, the initial results indicate that the ASTRA Bridge may become an integral part of future highway bridge refurbishment projects.
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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 | 0.001 | 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) | 0.003 | 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".