Effects of hydrolytic and freeze-thaw aging on the performance of spruce wood
Bibliographic record
Abstract
Abstract Wood is susceptible to various degradation mechanisms when exposed to dynamic environmental conditions, including hydrolysis caused by the infiltration of water into the wood cell structure. This study aims to examine the differences between the effects of two types of accelerated aging on the long-term performance of white spruce wood samples to have a better understanding of the performance of spruce wood in real-world applications. Two separate sets of samples were employed in this experimental study. One set was placed in a hydrolytic aging chamber at 90 °C and 80% relative humidity while the other set was placed in a freeze-thaw cycling chamber with temperature variations from 25 °C to -18 °C at a rate of 6 cycles per day. The aged samples were tested at regular intervals, with a testing span of 3 months for the hydrolytically aged samples and 300 cycles for the freeze-thaw aged samples. The results obtained from characterization tests showed that both aging conditions caused a significant increase in the crystallinity index of the samples. This finding highlights the potential value of subjecting wood to these conditions as a pre-treatment to standardize crystallinity levels for experimental purposes. Ultimately, the hydrolytic aging conditions were found to be more detrimental to the spruce wood samples. The samples that underwent hydrolytic aging demonstrated higher water uptake levels, lower viscoelastic properties, and lower thermal degradation temperatures than the samples that were subjected to freeze-thaw cycling.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".