Energy Streamlines Analyses on Natural Convection Within Porous Square Enclosure With Internal Obstructions
Bibliographic record
Abstract
Natural convection through a porous layer heated from the side with internal flow obstructions have been investigated based on visualization of total energy flow via energy streamfunctions or energy streamlines. Energy streamline has been introduced previously by Mahmud and Fraser (2007, “Visualizing Energy Flows Through Energy Streamlines and Pathlines,” Int. J. Heat Mass Transfer, 50, pp. 3990–4002) as an alternate convection heat transfer energy visualization technique. Energy streamlines consider all forms of related energy; for example, thermal energy, potential energy, kinetic energy, electrical energy, magnetic energy, and chemical energy. A finite volume method has been employed to solve momentum and energy balance as well as postprocessing energy streamfunctions. A parametric study has been carried out using the following parameters: Rayleigh number (Ra) from 103 to 106, Darcy number (Da) from 10−4 to 10−3, dimensionless thin fin lengths (L) 0.25, 0.5, and 0.75, dimensionless positions (H) 0.25, 0.5, and 0.75 with Prandtl number (Pr) 0.7. One finding of the present study is that, adding an obstruction in a cavity is similar to reducing Da of the porous medium. Therefore, the average Nusselt number calculated on the hot wall of the cavity always degraded compared to the no obstruction case whenever a baffle is attached. Thus the attached horizontal obstruction adds some thermal insulation effect. This finding is important in double wall space filled with fiberglass insulation in contemporary buildings, where the side wall is reinforced on the inside with structural members.
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 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) | 0.000 | 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".