EFFECT OF BONDING MATERIAL ON SURVIVABILITY OF SURFACE-ATTACHED EDDY CURRENT SENSORS
Bibliographic record
Abstract
Structural health monitoring relies on the correct functionality of surface-attached or embedded sensors to detect changes in the condition of the investigated part.Departures from a baseline signal indicate variations in the properties of the part, as for example, fatigue crack initiation and growth in cyclically loaded structures.In the case of printed circuit board, planar eddy current copper coils, special considerations have to be taken in order to assure that the sensing coil is properly operating in the high strain field of a growing crack.Bonding materials with appropriate elastic properties, used to attach the eddy current sensors to the structure, need to be carefully selected as to minimize load transfer from the part to the coil traces.Microcracking and fatigue of the coil material could locally modify the electrical resistance of the coil and provide erroneous damage indications.In this work, two adhesives of largely different stiffness are used to attach spiral eddy current coils meant to monitor growing fatigue cracks initiated from fastener holes in aluminum alloy specimens under cyclic uniaxial tensile stress.Only the more flexible adhesive material allowed survivability of the eddy current sensor.The rigid one is believed to facilitate load transfer from the metallic substrate, resulting in microcracking in the coil's traces that affect the electrical response supposed to indicate the damage growth.In this work, the empirical findings are supported by numerical simulation looking into variations of the bonding material stiffness and thickness.These outcomes are meant to aid in the selection of the adhesives that will assure proper functionality and survivability of the surface-attached eddy current sensors in structural health monitoring for damage detection applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.002 | 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 teacher head, 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".