Modeling Shrinkage Response to Tensile Stresses in Wood Drying: I. Shrinkage-Moisture Interaction in Stress-Free Specimens
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
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. Keywords: DryingFree shrinkageMoisture contentWestern hemlock ACKNOWLEDGEMENTS This research was financially supported by a Natural Sciences and Engineering Research Council of Canada CRD grant and by a Research Grant-in-Aid from FP Innovations, Forintek Division. The input regarding experimental design and data analysis by Dr. Tony Kozak is greatly appreciated. Notes ∗SD = standard deviation. Any two numbers not having the same subscript are significantly different.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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