Natural Convective Heat Transfer From Horizontal and Inclined Two-Sided Bodies of Finite Thickness
Bibliographic record
Abstract
Natural convective heat transfer from two-sided flat plates that are horizontal or inclined to the horizontal has been numerically and experimentally investigated. The objective of the study was to investigate the influence of changes in the plate thickness, of the boundary condition over the plate side surface, of the plate shape, and of the inclination angle on the heat transfer rate. A further objective was to investigate whether the heat transfer rate from a flat plate can be increased by using a plate having a non-flat surface. The heated elements considered were exposed to air. The heat transfer rate was numerically obtained by using the commercial CFD solver ANSYS FLUENT© and experimentally determined using the lumped capacity method. \nIn addition, natural convective heat transfer from bottom-heated rectangular enclosures that contain a nanofluid and which have various aspect ratios was numerically studied. The purpose was to determine whether the heat transfer rate from the heated bottom wall of the enclosure can be increased compared to that which would exist with pure water and to study the influence of the nanofluid nanoparticle concentration and of the enclosure aspect ratio on the heat transfer rate. \nThe results of the studies of natural convective heat transfer from heated plates indicated that the plate thickness and the thermal boundary condition have only a modest influence on the heat transfer rate from the bottom surface of the plate. The influence of the inclination angle on the heat transfer rate from the top surface of the plate is higher than its influence on that from the bottom surface. For the case of the plate having a non-flat surface, the results indicated that the heat transfer rate can be enhanced by using a non-flat surface but this enhancement is relatively small. \nThe results of the study of heat transfer across a nanofluid filled enclosure showed that the heat transfer rate is significantly increased by replacing pure water with a nanofluid (Cu-water) and by increasing the nanoparticle concentration. It was also found that the enclosure aspect ratio had only a small influence on the heat transfer rate.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".