Flow, Thermal, Energy Transfer, and Entropy Generation Characteristics Inside Wavy Enclosures Filled With Microstructures
Bibliographic record
Abstract
Flow, thermal, energy, and irreversibility characteristics inside wavy enclosures packed with microstructures are reported in this paper. It is assumed that the entire enclosure has sufficient and interconnected void spaces; those allow fluid movement inside the cavity. The Darcy momentum equation is selected for momentum transfer modeling by considering a relatively small pore Reynolds number (Rep). Modeled equations are solved numerically using the finite volume method. Streamlines, isothermal lines, energy streamlines, average Nusselt number, and average entropy generation number are calculated and displayed in order to show their dependency on and variation with Rayleigh number (Ra), surface waviness (λ), and aspect ratio (AR) of the enclosure. Depending on the wall waviness pattern, the enclosure is divided into three modes (phase-plus, phase-zero, and phase-minus modes). However, for the current calculation, wall waviness is kept symmetric with respect to the vertical and horizontal centerlines of the enclosure.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".