Fatigue Behavior under Rolling Load of a Full-Scale Bridge Deck with a Steel-Reinforced Section
Bibliographic record
Abstract
Fatigue tests were performed on a full-scale deck slab (15,240 × 3,890 × 210 mm) supported by steel girders spaced at 3.05 m using a rolling load simulator for up to 6 million equivalent cycles under two half axle moving loads of 90 kN each, spaced at 1.2 m. The loads were designed to produce the equivalent effect of the CL625 design truck of the Canadian Highway Bridge Design Code (CHBDC). The deck had several sections featuring three different reinforcement designs; namely, steel rebar, glass fiber–reinforced polymer (GFRP) rebar, and GFRP structural permanent form. The steel rebar was designed in accordance to the empirical method in Section 8 of the CHBDC. This paper focuses primarily on the performance of the 3,810 × 3,890 mm steel-reinforced section and compares it to the two adjacent GFRP-reinforced sections. It also introduces a method to define the loading cycle based on vertical deflection and recovery at the center of a section, which could differ from the vehicle travel cycles. As a result, it was shown that the middle steel-reinforced section experienced 6 million cycles, double that of the two end sections. It experienced a 71% reduction in stiffness and its live-load deflection increased by 2.36 times. The live-load strain of its bottom transverse reinforcement reduced from 384 to 264 με, while the strain of the top transverse reinforcement over the support increased from 20 to 301 με after 6 million cycles. The deflection limit of L/800 was satisfied up to 4.47 million cycles. A dense grid-pattern of cracks occurred at the bottom. Few transverse cracks occurred on top and longitudinal cracks developed above the girders.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".