Development of Concrete Link Slabs to Eliminate Bridge Expansion Joints Over Piers
Bibliographic record
Abstract
A primary factor affecting the durability of bridge structures is the use of expansion joints at bridge support locations. The inability of current joint systems to provide reliable and effective long-term leakproof performance generally leads to early leakage of chloride-contaminated water through those joints, causing premature corrosion at girder ends and supporting substructures. The Ministry of Transportation of Ontario has tried to eliminate the expansion joints during deck rehabilitation by using a number of approaches. Some of the systems that have been implemented in recent projects include: (i) converting the simply-supported spans into a semi-continuous deck system by encasing the girder ends in a monolithic transverse concrete diaphragm, (ii) linking the simple spans by a thin concrete slab (flexible link slab) that spans between haunched beam sections on either side of link slab while keeping the girders discontinuous; and (iii) using a similar link slab concept except that the link slab is debonded from the girders for a longer length at each girder end. The paper discusses the relative merits of these systems from both technical and economic standpoints and provides examples of recent field applications of each system. The practical lessons that were learned and the field performance of each system to date are also presented.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".