Monitoring and Assessment of Buckling in Slender Members with Varying Lateral Restraint and Thermal Loading Using Distributed Sensing
Why this work is in the frame
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Bibliographic record
Abstract
Buckling of slender members due to gravity loading or thermal effects is influenced by the member’s geometric imperfections, boundary conditions, and intermediate lateral supports. When assessing the capacity of such members, these parameters are often unknown (e.g., the rotational stiffness of end connections in a truss or the lateral support provided by the ties to a rail track), and conservative assumptions must be made resulting in conservative assessments. Distributed fiber optic sensors (DFOS) can potentially be used to determine these parameters with greater accuracy using strain measurements along the length of a member. A series of buckling experiments was conducted on a slender member instrumented with DFOS subjected to axial load with varying levels of lateral restraint or to increasing temperature. The distributed strain data were then used to evaluate the geometric imperfections, boundary conditions, and lateral support stiffness. These inputs were used to create a finite-element model to estimate the ultimate load response of the member using data acquired at service loads.
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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 | 0.000 | 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 | 0.001 |
| 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 it