Distributed sensing to assess the effect of axial restraint on reinforced concrete slabs
Bibliographic record
Abstract
Current design codes do not account for effects such as arching and membrane action in reinforced concrete slabs, which can increase capacity, and allow for a reduction of construction materials to be used. Research conducted to date has been unable to measure stress distribution throughout reinforced concrete slabs to fully understand the impact of arching and membrane action, because a method for capturing distributed strains was previously unavailable. One solution is to use distributed monitoring technologies to evaluate slab behaviour. Distributed fibre optic sensors (FOS) based on measuring Rayleigh backscatter provide strain measurement along the full length of the fibre up to 70 m. An experimental study using this technology was undertaken to investigate the behaviour of reinforced concrete slabs subjected to axial restraint. In the first test series, eleven one-way reinforced concrete slabs with varying depths, reinforcement ratios, and boundary conditions were instrumented with nylon coated FOS and tested in three-point bending to investigate the effects of axial restraint on slab behaviour. It was found that axial restraint increased the load carrying capacity of the specimens up to 45% and reduced reinforcement strains at a given applied load prior to yielding. An increase in capacity and decrease in reinforcement strains at a given load were also seen as reinforcement ratios and slab depths were increased. All specimens failed in flexure. In the second test series, four two-way reinforced concrete slabs with varying reinforcement ratios and boundary conditions were instrumented and tested under a central point load. Increasing the reinforcement ratio led to an increase in slab capacity up to 45%. Two specimens failed in flexure and two failed due to punching shear. Finite-element models were created for the one-way specimens to evaluate the accuracy of the models for use in structural assessment with distributed sensing. Plastic collapse analysis was completed for the two-way specimens in order to determine the accuracy of the analyses. Results from the FE model were accurate for the control specimens but showed stronger and stiffer responses compared to the restrained specimens. The plastic collapse analyses estimated the experimental control capacity within 13%.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".