The development of stamp points displacement mathematical model by static tests of road structures
Bibliographic record
Abstract
In various static stamp tests methods, both foreign and Ukrainian, it is foreseen to use a different number of sensors for stamp settlement measuring. Austrian method with three displacement sensors allows to reveal the stamp warping while loading, but it is unclear how to determine the settlement in the stamp center, when the sensor readings at the moment of warping will be completely different. The German method with a single displacement sensor is much simpler, but does not consider the stamp warping. The use of Ukrainian methodology is not appropriate at all, because two displacement sensors do not allow to observe the stamp warping. The article is focused on mathematical model for the displacement of stamp points in road structures static testing development with theoretical justification of necessary and sufficient number of sensors for stamp settlement measuring. Initially, the stamp displacement under warping in a flat deformed condition is considered as a rotation on a certain angle α and a parallel transfer. It has been established that in this case, the stamp settlement with enough accuracy for engineering practice can be measured with a single displacement sensor installed in the stamp center. In fact, the stamp can rotate not only around the axis Oy, but also around the Ox axis. Therefore, a separate mathematical model is constructed and describes the process of stamp displacement while it’s warping in a volumetric deformed condition. The developed mathematical model provides an opportunity to determine the settlement in the stamp center, necessary for the modulus of elasticity calculation or modulus of deformation in the case when the stamp at the warping moment will rotate both around the axis Oy and around the Ox axis, and the rotation angles α and β will be significant.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".