Sensitivity Study of a Numerical Model of Heat and Mass Transfer Involved During the Medium-Density Fiberboard Hot Pressing Process
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
The objective of this work was to estimate the impact of the variability of the mediumdensity fiberboard mat heat and moisture transfer properties on the results predicted by a numerical model of hot pressing.The three state variables of the model, temperature, air pressure, and vapor pressure, depend on parameters describing the material properties of the mat known with a limited degree of precision.Moreover, different moisture sorption models and initial moisture contents also have an impact on the numerically predicted results.In this sensitivity study, we determined the impact of variations of the mat properties, sorption models, boundary conditions, and initial MC on the state variables.Our study shows that mat thermal conductivity, convective mass transfer coefficient of the external boundary, and gas permeability have the most significant impact on temperature, gas pressure, and MC within the mat.On the other hand, the convective heat transfer coefficient of the external boundary has no impact on the state variables.The sorption model affects significantly mat MC predictions only.The initial MC of the mat has a strong influence on the internal gas pressure.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it