Structural health monitoring of innovative bridge decks
Why this work is in the frame
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Bibliographic record
Abstract
Abstract For more than a century, important civil engineering structures such as bridges, high-rise buildings, dams and marine platforms have contained iron or steel as the reinforcement for concrete or wood. The useful lives of such structures have often been severely limited by the corrosion of this ferrous component. Much thought has been given in recent years to constructing structures that are lighter, stronger and non-corrosive. These innovative structures are new and for these to be accepted by the engineering community monitoring is mandatory. ISIS Canada has been developing such structures and monitoring them. In this paper, innovative bridge decks that have been implemented are described. Keywords: Second-generation steel-free deck slabArching actionBridge deck slabStructural health monitoringFibre reinforced polymer, FRPFibre optic sensor, FOS Acknowledgments The author would like to thank Vector Construction and Earth Tech for their valuable assistance with the projects in Manitoba. Also, the financial assistance of NCE, ISIS Canada and NSERC towards the research reported in this paper is gratefully acknowledged. The fatigue testing of full-scale model deck slabs is part of the research that Mr Amjad Memon is currently conducting towards his Ph.D. The full-scale, second-generation, steel-free/GFRP hybrid bridge deck is part of the research being conducted by Mr Chad Klowak, who will be reporting his findings in his M.Sc. thesis ("The design, construction, and structural health monitoring of an innovative second generation steel-free/FRP hybrid bridge deck", University of Manitoba, Winnipeg, Manitoba, Canada.) Also, the collaboration of Dr Baidar Bakht and Dr Gamil Tadros is gratefully acknowledged. Notes First published online 11 March 2005. Additional informationNotes on contributorsAftab Mufti First published online 11 March 2005.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it