Developing a structural-health-monitoring model to monitor cracking in steel-free concrete deck slabs
Bibliographic record
Abstract
The ISIS Canada Networks of Centres of Excellence (NCE) program has focused on two main themes to improve civil engineering infrastructure, namely innovative construction technologies, and structural health monitoring (SHM). The former began with the construction of the first field application of the innovative steel-free concrete bridge deck slab technology at the Salmon River bridge, Nova Scotia, in 1995. Although this bridge has continued to function safely under heavy traffic loads, it has developed characteristic longitudinal cracking of the concrete between adjacent girders due to fatigue. This paper describes the recent research to develop an SHM model for monitoring the impact and stability of this cracking. Theoretical and experimental models were used to examine the change in response as cracking develops. A global load distribution matrix was proposed, and the variation in load distribution values with cracking was used to develop a cracking index that can be employed in monitoring the field structure.Key words: structural health monitoring, bridges, concrete, deck slabs, cracking, load distribution.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".