Particle resolved simulations of carbon oxidation in a laminar flow
Bibliographic record
Abstract
This work is devoted to the numerical study of the impact of the Reynolds number and the ambient gas temperature on the partial oxidation of a single moving coal particle. The model includes six gaseous chemical species, three semi‐global heterogeneous surface reactions, and three homogeneous gas reactions. The Navier–Stokes equations coupled with the energy and species conservation equations were used to solve the problem. The diameter of the particles considered was set up as 2 mm and 200 m. An analysis of the simulations related to the influence of particle Reynolds numbers on integral characteristics such as surface‐averaged carbon consumption rates revealed that the oxidation rate increases with increasing gas velocity, which is logical. However, the increase in the particle Reynolds number leads to the prolongation of the kinetically controlled regime from lower to higher temperatures, which is explained by the enhancement of the mass transfer between the particle and the surrounding gas. Using visualization of the temperature and species mass fraction distributions around the reacting particles predicted numerically, the three well‐known basic oxidation regimes, namely the diffusion‐controlled , transitional , and kinetically controlled regimes are described, taking into account the impact of the particle Reynolds number on the dynamics of oxidation. The influence of radiation in the gas phase on oxidation rates was studied numerically using P1 radiation model. Additionally the behaviour of heterogeneous Damköhler numbers, Thiele modulus and effectiveness factors depending on the ambient temperature and particle Reynolds number was analyzed and discussed.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".