Combustion behavior of single iron particles, Part II: A theoretical analysis based on a zero-dimensional model
Bibliographic record
Abstract
Following the ignition and solid-to-liquid phase transition of a fine (on the order of 10–100 µm in diameter) iron particle, the self-sustained combustion of a liquid-phase droplet of iron and its oxides takes place. The objective of the current work is to develop an interpretive and explanatory model for the liquid-phase combustion of a single fine iron particle. A zero-dimensional physicochemical model is developed assuming fast internal processes, such that the combustion rate is limited by the rate of external oxygen (O2) transport. The model considers a particle covered by a shell of liquid-phase FeO enclosing a core of liquid-phase Fe. Stefan flow and diffusion are considered for the gas-transport of O2, while the gas-transport of gas-phase Fe and FeO are calculated via diffusion only. The outward gas-phase Fe and FeO consume inward-transported O2 to stoichiometrically form hematite (Fe2O3), and the remaining oxygen that reaches the particle surface is entirely consumed to form liquid-phase FeO. The time history of simulated particle temperature shows consistent overprediction of the peak particle temperature when compared to experimental temperature measurements, indicating that the assumption of fast internal kinetics may be incorrect. The model is also unable to capture the apparent slow cooling rate observed in experiments. A further analysis is performed through a heuristic model with a calibrated reaction-rate law, where the internal diffusion of reactive Fe and O ions may become rate-limiting. The calibration of the pre-exponential factor in the Arrhenius term to match the experimental peak temperature yielded good agreement of time to peak temperature, as well as the slow cooling rate. The heuristic model considering internal diffusion predicts a plateau in peak temperature with increasing oxygen concentration. Possible uncertainties of the models, as well as future work, are discussed.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".