Enhancing Melting Heat Transfer in a Double Tube Enclosure: The Role of Perforated Disk Fin Configurations
Bibliographic record
Abstract
This study aims to enhance the thermal performance of latent heat thermal energy storage (LHTES) systems using phase change materials (PCMs) by introducing novel perforated disk fin configurations, overcoming PCMs’ low thermal conductivity while maintaining fixed fin material volume. Numerical simulations employ a finite volume solver tailored for phase change heat transfer to model phase transitions, and a pressure‐based algorithm to ensure stability across flow regimes. Adaptive time stepping captures dynamic temperature evolution without sacrificing accuracy. The strategic placement of small holes enhances both convective and conductive heat pathways within the PCM, reducing thermal resistance and boosting energy transfer rates. This configuration overcomes the low intrinsic thermal conductivity of PCMs, enabling rapid thermal storage and retrieval. Twelve distinct fin designs were numerically analyzed to evaluate the effects of staggered arrangements, hole diameters, and row layouts on PCM melting and solidification rates. The optimal configuration, featuring multiple staggered rows of small‐radius holes to maximize surface area and heat transfer, accelerated melting by 67% compared to conventional designs and by 29% relative to nonperforated fins. Perforated fins thus enable natural convection flow and enhanced heat transfer, significantly improving LHTES thermal performance.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".