Nanofluid flow and heat transfer due to natural convection in a semi-circle/ellipse annulus using modified lattice Boltzmann method
Post-publication record
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Bibliographic record
Abstract
Purpose This paper aims to numerically investigate the nanofluid flow, heat transfer and entropy generation during natural convection in an annulus. Design/methodology/approach The lattice Boltzmann method is used to simulate the velocity and temperature fields. Furthermore, some special modifications are applied to make the lattice Boltzmann method capable for simulation in the curved boundary conditions. The annulus is filled with CuO-water nanofluid. The dynamic viscosity of nanofluid is estimated using KLL (Koo-Kleinstreuer-Li) model, and the nanoparticle shape effect is taken account in calculating the thermal conductivity. On the other hand, the local/volumetric entropy generation is used to show the irreversibility under influence of different parameters. Findings The effect of considered governing parameters including Rayleigh number (103 Originality/value The originality of this work is using of lattice Boltzmann method is simulation of natural convection in a curved configuration and using of Koo–Kleinstreuer–Li correlation for simulation of nanofluid.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".