An Optimal Thermo-Hydro-Mechanical Densification (THM) Process for Densifying Balsam Fir Wood
Bibliographic record
Abstract
To better utilize low-density softwood, a thermo-hydro-mechanical densification process performed in an open system was studied to enable the manufacture of densified wood with a hard surface, strong bonding, and good dimensional stability. This study was aimed at optimizing three densification parameters, i.e., compression ratio (CR), temperature, and time, for balsam fir (Abies balsamea (L.) Mill.). The Brinell surface hardness, bond strength, and thickness recovery ratio of densified fir were examined. It was found that the optimal densification parameters were a CR of 60%, a temperature of 230 ºC, and a time of 20 minutes. The surface hardness and bond strength of optimized densified fir were about 30 and 8 MPa, respectively. The thickness recovery ratio of the densified fir after a 2-hour cold water soaking and another 2-hour boiling treatment was about 10%. Because the densified fir in this study was used for indoor applications only, its thickness recovery ratio could be minimal under conditions of use.
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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 | 0.000 |
| 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) | 0.001 | 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".