Computational analysis of the reacting flow in a microstructured reformer using a multiscale approach
Bibliographic record
Abstract
A multiscale methodology is presented to analyze the transport and reaction processes in the catalyst coating of a microstructured reformer and to elucidate the effect of catalyst morphology on transport limitations and the reformer performance. This analysis includes three‐dimensional simulations of methane steam reforming at both reactor level (macroscale) and catalyst microstructure level (microscale). Hypothetical catalyst microstructures are generated using an in‐house particle packing code. Based on the generated structures, the effective transport properties of the porous catalyst and the average reaction rates in the microstructure are determined to be applied in the pseudohomogeneous model used in the macroscale simulation. Parametric study is done to demonstrate the significant effect of the catalyst intraparticle and interparticle porosity as well as the particle size on the reaction effectiveness factor and methane conversion. This study shows that an optimal catalyst coating has a decreasing porosity along the reformer length based on the difference in the degree of diffusion limitation. © 2014 American Institute of Chemical Engineers AIChE J , 60: 2263–2274, 2014
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".