Latent Heat Thermal Storage in Non-Uniform Metal Foam Filled with Nano-Enhanced Phase Change Material
Bibliographic record
Abstract
The melting heat transfer of CuO—coconut oil embedded in a non-uniform copper metal foam—was addressed. Copper foam is placed in a channel-shaped Thermal Energy Storage (TES) unit heated from one side. The foam is non-uniform with a linear porosity gradient in a direction perpendicular to the heated surface. The finite element method was applied to simulate natural convection flow and phase change heat transfer in the TES unit. The results showed that the porosity gradient could significantly boost the melting rate and stored energy rate in the TES unit. The best non-uniform porosity corresponds to a case in which the maximum porosity is next to a heated surface. The variation of the unit placement’s inclination angle is only important in the final stage of charging, where there is a dominant natural convection flow. The variation of porous pore size induces minimal impact on the phase change rate, except in the case of a large pore size of 30 pore density (PPI). The presence of nanoparticles could increase or decrease the charging time. However, using a 4% volume fraction of nanoparticles could mainly reduce the charging time.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".