MACKENZIE RIVER TWIN BRIDGES - THE LARGEST FIELD-CAST UHPC CONNECTIONS PROJECT IN NORTH AMERICA
Bibliographic record
Abstract
The Mackenzie River Bridges are part of the new Tra nsCanada Highway realignment near Thunder Bay, Ontario, Canada. The project consists of twin, two-lane bridges, each with three-spans for a total length of 180 m (590 ft-6 in). The bridges cross a deep gorge of the Mackenzi e River using variable depth, continuous steel plate girders with full-dep th precast deck panels that are lightly prestressed and run the full-width of t he bridge. Precast approach slabs and 130 precast deck panels (2.99 m [9 ft-7 i n]wide x 14.5 m [47 ft-7 in] long x 225 mm [9 in) thick) were jointed together in transverse joints and attached to the steel girders through shear pockets and haunches, using fieldcast ultra-high performance concrete (UHPC). With a total of 175 m 3 (229 yd 3 ), this application is the largest UHPC field-cast project in North America. This paper presents: a completed project profile; p recast deck panel details; and design of precast deck panel joints that utiliz e UHPC’s unique combination of superior properties in conjunction w ith precast deck panels. The benefits, such as improved resiliency and durab ility, reduced joint size, elimination of post-tensioning and extended usage l ife, are discussed. Additionally, the advantages realized by the owner (when using a precast bridge system with UHPC joints) are illustrated. The material properties, plus batching, casting and installation of this large field-cast UHPC project are illustrated. The advan tages of using this system and other UHPC field-cast connections for future br idge projects (especially for ABC construction) are also explored.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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".