A novel technique in mechanical evaluation of adhesive joints subject to monotonic and fatigue loading
Bibliographic record
Abstract
Adhesive joints are normally subject to static and fatigue loadings in their entire service-life duration. Various types of mechanical tests are needed in order to evaluate the joint performance under different working conditions that might also involve environmental degradation and mixed-mode loading. In this work, a series of cyclic tests on double-cantilever-beam (DCB) specimens have been conducted under opening loads (mode-I) at room temperature. The main objective of this work was to evaluate the mechanical performances of a toughened structural epoxy adhesive of 3M under monotonic and fatigue loadings. DCB specimens were made from aluminum bars in accordance with ASTM standard D 3433 and then tested by implementing a novel testing technique. A series of crack detection sensors (Vishay CD-23-IOA) were bonded to one face of DCB specimen and were used for crack length measurements and also for controlling the testing machine in switching between quasi-static and fatigue load cases. The testing machine had two aligned hydraulic actuators applying bending forces on upper and lower arms of DCB specimen. Five constant-amplitude cyclic tests were carried out on the same specimen in load control with a load ratio of 0.1. Prior to each cyclic loading, the quasi¬static value of critical strain energy release rate (C/c) in adhesive layer was first determined. The influence of testing frequency was also investigated by varying the testing frequency from 4 to 20 Hz. The fatigue performance of each configuration was represented by a power law relationship and was compared for different frequencies. The test results revealed that the fatigue damage occurred at lower load levels when compared with quasi-static fracture loads. The influence of fatigue loading on mechanical performance of adhesive joints should be considered in adhesive joint design.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".