Thermal conductivity and contact resistance of metal foams
Bibliographic record
Abstract
Accurate information on heat transfer and temperature distribution in metal foams is necessary for design and modelling of thermal-hydraulic systems incorporating metal foams. The analysis of heat transfer requires determination of the effective thermal conductivity as well as the thermal contact resistance (TCR) associated with the interface between the metal foam and the adjacent surfaces/layers. In this study, a test bed that allows the separation of effective thermal conductivity and TCR in metal foams is described. Measurements are performed in a vacuum under varying compressive loads using ERG Duocel aluminium foam samples with different porosities and pore densities. Also, a graphical method associated with a computer code is developed to demonstrate the distribution of contact spots and estimate the real contact area at the interface. Our results show that the porosity and the effective thermal conductivity remain unchanged with the variation of compression in the range 0–2 MPa; but TCR decreases significantly with pressure due to an increase in the real contact area at the interface. Moreover, the ratio of real to nominal contact area varies between 0 and 0.013, depending upon the compressive force, porosity, pore density and surface characteristics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".