Distributed Sensing to Assess the Behaviour of Dynamically Loaded Reinforced Concrete Beams
Bibliographic record
Abstract
The assessment of reinforced concrete (RC) structures has been inherently limited by the lack of adequate sensing technologies, which can capture both the global and localized behaviour of these complex composite systems. The inability to properly assess these structures, and understand their behaviour under static and dynamic loads, can result in costly rehabilitation or replacement of existing structures and potentially unnecessary conservativeness in future designs. To improve on traditional assessment methods, this thesis investigates the application of a new fibre optic sensing system, which is capable of accurately measuring dynamic and distributed strains throughout the length of a fibre optic cable. An experimental campaign was conducted, which included the design, construction and testing of 4 slender and 4 deep RC beams. The purpose of these tests was to evaluate the durability and accuracy of dynamic distributed fibre optic sensors (DDFOS) under dynamic loading, as well as to utilize the DDFOS results to develop a better understanding of the behaviour of RC beams under both cyclic and ultimate loads. The results showed that the fibre optic sensors could withstand the repeated loading as well as ultimate loads while accurately measuring distributed strains along the steel reinforcement within the RC specimens. This data provided key insights into the change of load carrying mechanism (from beam action to arch action) as well as the failure mechanisms. Two case studies were also conducted on existing RC beams within a building. The studies included the in-situ dynamic loading of the beams while monitoring them with both DDFOS technology and tradition discrete sensors. Jumping tests were carried out to provide dynamic loading on each beam. The detailed DDFOS data was assessed by comparing the results to the traditional sensors, and was used to determine critical performance metrics of the RC beams including: maximum strains, support conditions, and cracking behaviour. The data was further used to provide dynamic estimations of the changing distributed deflections and crack widths due to the application of the dynamic loads.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".