Extended Non-Destructive Testing of Composite Bonds
Bibliographic record
Abstract
Composite materials are increasingly being used in the manufacturing of structural components in aeronautics industry. A consequent light-weight design of CFRP primary structures requires adhesive bonding as the optimum joining technique but is limited due to a lack of adequate quality assurance procedures. The successful implementation of a reliable quality assurance concept for adhesive bonding within manufacturing and in-service environments will provide the basis for increased use of lightweight composite materials for highly integrated aircraft structures thus minimizing rivet-based assembly. The expected weight saving for the fuselage airframe is remarkable and therefore the driver for research and development of key-enabling technologies. The performance of adhesive bonds mainly depends on the physico-chemical properties of adherend surfaces. Therefore, a set of advanced non-destructive testing techniques is applied and adapted to the characterization of CFRP bonded structures as well as the state of adherend surfaces before bonding within the ENCOMB-project. As a medium-scale European Consortium funded within the 7th Framework Programme, ENCOMB (Extended Non-Destructive Testing of Composite Bonds) brings together leading experts in aeronautics research and development providing advanced non-destructive testing methods for reliable quality assurance of adhesive bonds of CFRP structural components. In the following results of two promising measuring techniques both from the field of characterization of adhesive bonds and adherend surface characterization are presented. It is expected that these technologies will have a major contribution to the quality assurance of adhesive bonding in the future.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".