Acoustic emission monitoring of reinforced concrete beams repaired with engineered cementitious composites
Bibliographic record
Abstract
In this thesis, acoustic emission (AE) monitoring was employed to analyze, characterize, and quantify the cracking behavior of a total of thirteen large-scale reinforced concrete (RC) multi-layered beams under flexural testing. The experimental work performed in this thesis was divided into two studies. In the first study, four RC beams were repaired with engineering cementitious composites (ECC) in either the tension zone or the compression zone of the beam. Two types of fibers were used in the ECC repair material: polyvinyl alcohol fiber (PVA) and steel fiber (SF). Three control beams (reference beams used for comparison) were tested for comparison including one normal concrete beam and two fully cast ECC beams with PVA and SF. AE parameters such as number of hits, cumulative signal strength (CSS), signal amplitude, peak frequency, absolute energy, and b-value (defined as the log-linear slope of AE’s frequency-magnitude distributions) were considered and used to evaluate the cracking behavior of both the repaired and unrepaired beams. Furthermore, rise time/maximum amplitude (RA) vs. average frequency (AF) analysis was implemented to categorize different failure modes (flexural, shear, or debonding). Varying the fiber type as well as sensor location/repair location seemed to have a significant effect on the signal amplitude and number of hits. With the aid of analyzing AE parameters (number of hits, CSS, and b-value), the first crack for all tested beams was successfully determined in the seven tested beams. In the second study, the flexural testing of four ECC multi-layered beams incorporated either crumb rubber (CRECC) or powder rubber (PRECC). Four beams were repaired in either the tension zone or the compression zone of the beam. Three beams were fully cast in normal concrete, CRECC, and PRECC, and were used as control beams (reference beams used for comparison). A variety of AE parameters such as number of hits and CSS as well as b-value were used to analyze the crack propagation of the tested beams. Damage quantification charts pertaining to different cracking stages (first crack and ultimate load), based on historic index [H (t)] and severity [Sr], were created in this study to categorize and quantify damage severity in terms of crack growth in composite beams. Alternating the rubber particle size, repair location or sensor location resulted in noticeable variations in the AE parameters (signal amplitude, CSS, and number of hits). For both studies, the addition of a new concrete layer (ECC incorporating fiber and/or rubber particles) seemed to result in a noticeable effect on AE parameters such as signal amplitude. In addition, varying the strengthening location, sensor location, and fiber type/ rubber particle size showed an impact on several AE parameters including number of hits, CSS, and b-value. By carrying out the AE analyses mentioned, the first crack identification for both the repaired and unrepaired beams was possible. Damage quantification and failure mode classification charts were successfully obtained by intensity analysis and rise time/amplitude analysis.
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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 | 0.000 | 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) | 0.000 | 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 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".