Finite difference solution for radiative–conductive heat transfer of a semitransparent polycarbonate layer
Bibliographic record
Abstract
Abstract Thermal radiation greatly affects the transient thermal response of translucent materials in many practical applications, such as radiative heat shields and ignition and flame spreads for translucent plastics. However, because of the complexities that transients impose, less work has been done on the transient analysis of combined radiation–conduction heat transfer than on steady‐state analysis. In this study, the transient heat transfer analysis of a polycarbonate (PC) layer was done with the use of the two‐flux method and implicit finite difference formulations. The radiative and conductive properties of PC available in the literature, together with computer implementation prepared on the basis of the two‐flux method and implicit finite difference formulations, were used to obtain the transient thermal response of a PC layer. On the basis of these results, we show that, compared to the conduction‐alone case, the PC layer responded faster when radiation effects were considered. It is also shown that the internal reflectivity of boundaries had a great effect on the thermal response of the layer, whereas the thermal conductivity had a minor influence. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".