The effect of radiation on the laminar natural convection induced by a line heat source
Bibliographic record
Abstract
Purpose To show the effect of radiation from the heat source and the variation of fluid properties on the laminar natural convection induced by a line heat source. Design/methodology/approach The governing equations – Navier‐Stokes and energy equation are discretized in a staggered grid by a control volume approach, and they are solved using a segregated technique. The equations for the fluid and solid (line heat source) phases are solved simultaneously. The three sides of the computational domain are open boundary. Some of the physical and thermo‐physical properties of the fluid (air) such as density, thermal conductivity and viscosity were considered to vary with temperature. Findings The present predictions are compared with those using the Boussinesq approximation, with the results for the boundary layer equations, and with the experimental results. The present predictions reveal considerable departure from the Boussinesq‐based solution and from the boundary layer results. This study also shows the radiation exchange between the heat source and surrounding has major effect in the results. Thus, the departure between the experimental and analytical results can be explained by the effect of radiation exchange. Research limitations/implications In this work, just studied steady‐state laminar thermal plume with the effects of radiation from heat source and the variation of air properties with temperature while it is propose to extend this work to transient and/or turbulent flow. Originality/value The effect of radiation from a line heat source on the flow filed around the source and offers enhancement of design to thermal engineers.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".