Modelling of particulate matter transformations and capture efficiency
Bibliographic record
Abstract
In the current work, a comprehensive computational fluid dynamics (CFD) model is developed for an accurate description of the transport and transformation of automotive particulate matter (PM) in monolithic reactors. The model accounts for the developing gas flow, the evaporation of hydrocarbons (HCs) from the particles, and the adsorption of HCs in the washcoat, as well as motion, shrinkage, and deposition of particles in the channel. The comprehensive CFD model is used to validate a simplified tanks‐in‐series approach with a conceptual model for PM transformations. In the development of more detailed and accurate chemical kinetics for the reactions of PM in filters, it will be necessary to also predict the time‐resolved properties of the particles collected in the filter (e.g., reactivity, amount of adsorbed HCs). It is shown in this work how the data necessary to construct such models can be obtained in situ with the aid of the conceptual model and PM measurements over an inert open substrate.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".