Chemical‐looping combustion process: Kinetics and mathematical modeling
Bibliographic record
Abstract
Abstract Chemical Looping Combustion technology involves circulating a metal oxide between a fuel zone where methane reacts under anaerobic conditions to produce a concentrated stream of CO 2 and water and an oxygen rich environment where the metal is reoxidized. Although the needs for electrical power generation drive the process to high temperatures, lower temperatures (600–800°C) are sufficient for industrial processes such as refineries. In this paper, we investigate the transient kinetics of NiO carriers in the temperature range of 600 to 900°C in both a fixed bed microreactor (WHSV = 2‐4 g CH 4 /h/g oxygen carrier) and a fluid bed reactor (WHSV = 0.014‐0.14 g CH 4 /h per g oxygen carrier). Complete methane conversion is achieved in the fluid bed for several minutes. In the microreactor, the methane conversion reaches a maximum after an initial induction period of less than 10 s. Both CO 2 and H 2 O yields are highest during this induction period. As the oxygen is consumed, methane conversion drops and both CO and H 2 yields increase, whereas the CO 2 and H 2 O concentrations decrease. The kinetics parameter of the gas–solids reactions (reduction of NiO with CH 4 , H 2 , and CO) together with catalytic reactions (methane reforming, methanation, shift, and gasification) were estimated using experimental data obtained on the fixed bed microreactor. Then, the kinetic expressions were combined with a detailed hydrodynamic model to successfully simulate the comportment of the fluidized bed reactor. © 2010 American Institute of Chemical Engineers AIChE J, 2010
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 0.001 |
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".