An unconventional barrier design
Bibliographic record
Abstract
An industrial project in northern Canada was recently completed that required multiple ultra-heavy loads to be carried by the world’s largest mine trucks over a new bridge structure. The truck’s Gross Vehicle Weight (GVW) was 6134 kN exceeding typical highway loads by more than 10 times. A rectangular concrete structure with two cells was selected as the most cost-effective option due to site constraints. The main access road consists of two single standard width traffic lanes travelling under the proposed bridge. Traffic on the access road is comprised of light vehicle traffic. The bridge overpass had three lanes, each with a 20 m wide diving lane. The span of the overpass was 71 meters. Highway bridge codes do not provide guidance for barrier design appropriate to restrain heavy haul trucks. Crash test results are not available for barriers capable of withstanding these loads. This presented challenges in structural analysis and design and in the design of safety components, including safety barriers. Therefore, the geometry of the barrier, the structural design, and the support of these barriers by the bridge superstructure required advanced modelling and design. As a safety requirement for the project, the oversize barriers are designed to redirect the heavy haul trucks in the event of a collision. Other challenges with this unique structure include rockfall simulation to model rock freefall for regular traffic below. Any debris generated on the overpass, including haul truck material, has the potential to free fall from the top haul truck boxes and impact light-duty vehicles travelling under the bridge on the highway traffic main access road. Stantec completed a quantitative rockfall simulation to mimic the trajectory of rocks or hardened soil clumps falling from the haul trucks and provided recommendations for mitigation measures. As a result, an engineered rockfall fence was built to capture rocks and debris. This paper presents some of the challenges of this unique heavy-load design and construction project.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".