Square Heating Applied to Shearography and Active Infrared Thermography Measurements Coupling: From Feasibility Test in Laboratory to Numerical Study of Pultruded CFRP Plates Glued on Concrete Specimen
Bibliographic record
Abstract
ABSTRACT This paper investigates thermography and shearography couplings, using feasibility trials and numerical simulations, for non‐destructive control evaluations of bonding of carbon fiber‐reinforced polymer plates glued over concrete structures. Those are well‐known methods in non‐destructive testing (NDT) applied to civil engineering, but in this context, they are seen as paired because they use the same excitation source: square‐pulsed optical heating. Furthermore, because both methods are based on different properties, the detection of defects is optimised regardless of its nature or type. The combination of the methods allows the measurement of a thermal as well as a thermomechanical response from the structure at the same time. A quick review of those methods and their respective advantage and inconvenient is mentioned. An in‐depth study of the interpretation of the thermal and mechanical responses is carried out in relation to the thermal excitation. Then, the thought process behind the conception of the finite element model and its limitation is discussed. The experimental setup, used for feasibility testing, is described as well as a thorough analysis of the experimental and simulated results. Finally, the pairing of both methods is discussed regarding the evaluation of the bond quality, as well as the similitude of the sample and its numerical model.
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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) | 0.000 | 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) | 0.001 | 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".