Bibliographic record
Abstract
Airflow and heat/mass transfer in a woodkiln are simulated numerically. The uniformity of drying and the quality of the wood in a kiln are strongly influenced by the airflow. A numerical model that simulates the airflow distribution is described and applied to solve the flow distribution in a kiln. The influences of the gaps between lumber pieces and the unevenness of lumber height on the velocity distribution and heat/mass transfer in the woodkiln are investigated numerically. A mathematical model for heat and mass transfer during the wood drying process is presented. The influence of kiln temperature, humidity and transport properties of wood is numerically investigated. The three key parameters in the model are moisture content M , temperature T and total pressure P in the gaseous phase. The results are compared with drying rate experiments carried out by Forintek Canada Corporation. Numerical model predictions are in satisfactory agreement with experimental results. Airflow and wood drying models are coupled to carry out a complete calculation. The model will constitute a powerful tool to optimize kiln design and to help operators improve kiln operations without entailing major new costs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".