Numerical modeling of the medium-density fiberboard hot pressing process. Part 1, Coupled heat and mass transfer model
Bibliographic record
Abstract
A mathematical model describing heat and moisture transfer during hot pressing of medium-density fiberboard mats is presented. The model is based on conservation of energy, air mass, and water vapor mass, resulting in a three-dimensional unsteady-state problem in which mat properties and state variables vary in time and space. The conservation equations are expressed as functions of the three state variables: temperature, air pressure, and vapor pressure. The model includes conductive and convective heat transfer, phase change of water, and convective and diffusive mass transfer. Resin curing kinetics and latent heat associated with phase change of water are also taken into account. The closing of the batch press and development of the density profile are taken into account by imposing a predefined time- and space-dependent density profile. Calculations are carried out on reference geometry, and mathematical details relevant to the transfer from actual to reference geometry are presented. The system is discretized in space by the finite element method and in time by the Euler implicit scheme. The results exhibit good agreement with experimental measurements and provide information on variables of interest such as total gas pressure, temperature, moisture content, RH, and resin cure.
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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 | 0.001 |
| 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".