Application of Flat-Clad Optical Fiber Bragg Grating Sensor in Characterization of Asymmetric Fatigue Deformation of Extruded Magnesium Alloy
Bibliographic record
Abstract
We report the application of a novel flat-cladding optical fiber Bragg grating sensor array in the characterization of low cycle fatigue deformation behavior of an extruded AZ31 magnesium alloy. The results obtained from optical fiber sensors showed strong asymmetry of stress-strain hysteresis loops, especially at high strain amplitudes, due to the occurrence of twinning in compression and detwinning in tension. At a given total strain amplitude, the degree of asymmetry of the hysteresis loops decreased with increasing number of cycles. The alloy also exhibited strong cyclic hardening at higher total strain amplitudes. All of these observations were in good agreement with those measured from an extensometer, and with those reported in the literature. In particular, the plastic strain amplitudes evaluated from optical fiber sensors demonstrated a nearly perfect agreement with those obtained from the extensometer, further corroborating the suitable use of the optical fiber sensors as an important tool in the evaluation of cyclic defromation behavior of materials.
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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".