Pier Repair/Retrofit Using UHPC—Examples of Completed Projects in North America
Bibliographic record
Abstract
The infrastructure sector is under tremendous pressure to find reliable and durable solutions to tackle maintenance and upgrade existing structures to meet our ever changing needs. Owners and designers need to select repairs and retrofits solutions that are proven and which will perform as intended for the remaining life of the structure. Ultra-High Performance Concrete (UHPC) sold under the brand name Ductal® by Lafarge North America Inc. (a member of LafargeHolcim) has been used throughout North America for over 15 years. The design community is increasingly familiar with the UHPC closure pour solutions for precast deck panels. This is now leading consultants to push the envelope and explore avenues where the durability of UHPC can be applied to other types of bridge repairs. This paper will provide a brief overview of four North American pier repair/retrofit projects. The CN Rail, Montreal, QC jacketing project; the Mission Bridge, Abbotsford, BC seismic pier retrofit; the Hooper Rd., Town of Union, NY connection of a new precast pier cap to existing columns; and the Hagwilget Bridge, New Hazelton, BC steel bent legs encasements will be reviewed. These “new” projects are now becoming references to guide owners and designers facing similar challenges where viable, durable and maintenance free solutions are required.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".