Suitability of DIC in capturing flexural behaviour of as-built and CFRP-strengthened RC beams
Bibliographic record
Abstract
In this paper, the suitability of digital image correlation (DIC) technology in evaluating the flexural behaviour of as-built and carbon-fiber-reinforced polymer (CFRP) strengthened reinforced concrete beams was verified by conducting a four-point bending test on four large-size beams. The DIC data obtained during the tests were compared to the results measured using traditional techniques such as displacement sensors and electrical strain gauges, as well as the findings derived from finite element (FE) numerical simulations. A good agreement was achieved between the local displacement and strain measurements and the data from DIC as a function of the applied load. Moreover, the crack patterns generated by the FE modelling were validated by the corresponding patterns derived from DIC. This suitability study is expected to contribute to the future field implementation of DIC technology to monitor the CFRP-strengthened members of critical structures such as bridges.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".