DETECTION OF MATERIAL PROPERTIES IN A LAYERED BODY BY MEANS OF THERMAL EFFECTS
Why this work is in the frame
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Bibliographic record
Abstract
The article discusses an algorithm developed for the detection of material properties and thickness of a layered solid body. The algorithm combines system equations and data from measurements taken in time intervals. The heat conduction equation, uncoupled thermoelasticity equations, and equations of motion (elastodynamic equations) are used to formulate an optimal estimation problem that seeks to minimize the error difference between the given data and the response from the system. Since all measurement instruments are error prone, the influence of an artificially generated measurement error on the accuracy of the solution is investigated. The method leads to an iterative algorithm that at every iteration requires the solution of a two-point boundary value problem. The numerical results indicate that a close estimate of the unknown material properties and thickness of the three-layered body can be obtained based on the displacement and temperature measurements on a temporal interval. The method was tested on the simulated experimental data.
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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 | 0.000 |
| 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 it