Minor defect correlation with dynamic elastic properties of polypropylene fiber-reinforced concrete
Bibliographic record
Abstract
The efficient rehabilitation of aging civil infrastructure requires innovative and emerging materials along with the proper implementation of structural health monitoring (SHM). Prior to identifying a strategic SHM technique, the understanding of defects in structures is vital. Common defects in concrete include consolidation problems and the development of microcracks during consolidation or stress induction. Monitoring the dynamic characteristics of concrete can play an essential role in detecting real-time and early stages of deterioration. Much research is focused on detecting large defects; however, not much information is available on the detection of minor defects in composites such as fiber-reinforced concrete. This study focuses on testing and monitoring of the dynamic elastic behavior of concrete using a non-destructive resonant frequency approach. The change in dynamic elastic properties of normal concrete under flexural and compression loading is analyzed. Moreover, an initial attempt to monitor the change in the elastic behavior when polypropylene fibers are added as reinforcement is also investigated. Experimental results show a decrease in the dynamic modulus of elasticity when minor defects are present and when polypropylene fibers are added to plain concrete mixture.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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; both teacher heads agree on what is shown here.
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".