Two-Region Fin Model Adjacent Temperature Profile Interactions
Bibliographic record
Abstract
Recent theoretical developments in steady-state heat conduction modeling of multilayer composite materials (i.e., laminates) subject to non-uniform heating from constant temperature and constant heat flux heat sources have revealed the importance of detailed modeling in the heat spreading, inner high-thermal conductivity layer only. The two-region fin model has already demonstrated this behaviour with experimental and numerical validation in Cartesian and cylindrical coordinates and both kinds of heat sources, but the heat spreading region (i.e., fin region) was considered as an infinite domain. Important applications of laminate heat spreading do not conform to this condition, and therefore further development has been undertaken to model the behaviour in Cartesian coordinates with an insulated boundary condition in the fin region. The new heat conduction and temperature profile equations show that the proximity of the insulated boundary in the fin region enhances temperature uniformity over the laminate system’s surface. An insulated boundary in the fin region can either arise from a physical boundary (with known location) or from the interference of an adjacent two-region fin region domain (location inferred). A technique of superposition is proven and demonstrated to determine the location of the insulated boundary in the fin region caused by an adjacent domain, and a new temperature uniformity parameter is derived and its use is demonstrated in the design and modeling of laminateencapsulated phase change material heat exchangers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".