Acoustic emission monitoring for bond integrity evaluation of reinforced concrete under pull-out tests
Bibliographic record
Abstract
This article presents the results of an experimental investigation on the application of acoustic emission technique for monitoring the steel-to-concrete bond integrity of reinforced concrete structures. A series of direct pull-out tests were performed on 54 reinforced concrete unconfined prism samples with variable rebar diameter (10, 20, and 35 mm), embedded length (50, 100, and 200 mm), and concrete cover (20, 30, and 40 mm). The samples were tested under incrementally increasing monotonic loading while being continuously monitored via attached acoustic emission sensors. These sensors were utilized to acquire different acoustic emission signal parameters emitted throughout the tests until failure. Also, an acoustic emission intensity analysis was implemented on acoustic emission signal strength data to quantify the damage resulting from loss of bond in all tested specimens. This analysis employed the signal strength of all recorded acoustic emission hits to develop two additional parameters: historic index ( H ( t)) and severity ( S r ). The results of bond behavior, mode of failure, and free end slip were compared with the recorded acoustic emission data. The results showed that the cumulative number of hits, cumulative signal strength, H ( t), and S r had a good correlation with different stages of bond damage from de-bonding/micro-cracking until bond splitting failure and bar slippage, which caused cover cracking or delamination. The analysis of cumulative signal strength and H ( t) curves enabled early identification of two progressive stages of bond degradation (micro-cracking and macro-cracking) and recognized the various modes of failure of the tested specimens. The variations of bar diameter, concrete cover, and embedded length yielded significant impacts on both the bond behavior and acoustic emission activities. The results also presented developed intensity classification charts, based on H ( t) and S r , to assess the bond integrity and to quantify the bond deterioration (micro-cracking, macro-cracking, and rebar slip) in reinforced concrete structures.
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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 | 0.001 | 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 | 0.000 | 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".