The effect of surface regression on the downward flame spread over a solid fuel in a quiescent ambient
Bibliographic record
Abstract
The present work is addressed to the numerical study of the transient laminar opposed-flow flame spread over a solid fuel in a quiescent ambient. The transient governing equations - full Navier-Stokes, energy, and species (oxygen and volatiles) for the gas phase, and continuity and energy equations for the solid phase (fuel) with primitive variables are discretized in a staggered grid by a control volume approach. The second-order Arrhenius kinetics law is used to determine the rate of consumption of volatiles due to combustion, and the zero-order Arrhenius kinetics law is used to determine the rate of degradation of solid fuel. The equations for the fluid and solid phases are solved simultaneously using a segregated technique. The physical and thermo-physical properties of the fluid (air) such as density, thermal conductivity, and viscosity vary with temperature. The surface regression of the solid fuel is modeled numerically using a discrete formulation, and the effect upon the results is analyzed. The surface regression of the solid fuel as shown affects on the fuel surface and gas temperature, mass flux and velocity of volatiles on the top surface of fuel, total energy transferred to the solid phase, etc. It seems the results to be realistic. .
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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 | 0.002 |
| 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 | 0.001 | 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".