Modeling Shrinkage Response to Tensile Stresses in Wood Drying: I. Shrinkage-Moisture Interaction in Stress-Free Specimens
Bibliographic record
Abstract
This article reports on the wood shrinkage during drying in relationship with the temperature and moisture content. All tests were performed perpendicular to the grain on small clear wood specimens of green Western hemlock while drying at 40, 60, and 80°C to 17, 11, and 5% final moisture contents. Overall, wood dimensional changes and moisture loss phenomena were successfully analyzed and interpolated. The shrinkage strain followed a nonlinear pattern with the moisture loss being the driving force and exhibited good correlation with the square value of moisture content in tangential, and linear moisture values could be used to describe shrinkage in radial direction. Both shrinkage intersection points and end of capillary water values increased with temperature; the distinction between the two values could not be made at all times. A nonlinear function containing two regression coefficients (α and β) was found to be a good interpolation of the moisture loss experimental data. Further analyses revealed that β is independent of both target moisture content and temperature, whereas α appears to be influenced by both variables. The correlation between shrinkage and moisture loss rate is intended to be used as a stress prediction tool.
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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 | 0.001 |
| 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) | 0.001 | 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".