Simulations of Binary Particles Distributions in a Separated-Gasification Chemical Looping Combustion System
Bibliographic record
Abstract
Chemical looping combustion is a promising non-flame combustion technology which can separate CO2 during combustion process without extra energy penalty [1].Previous, a separated-gasification chemical looping combustion system was designed and constructed, which consisted of a gasifier (GR), a reduction reactor (RR) and an air reactor (AR) [2].The results of hot operation showed satisfying CO2 yield.In order to know the detailed gas-solid flow characteristics, a threedimensional computational fluid dynamics (CFD) model was adopted to predict the multiphase hydrodynamics.In the cold operation of this system, there are three phases, gas, coarse sand particle and oxygen carrier.The sand particle bubbles in GR while the oxygen carrier circulated between RR and AR.The detailed operation mechanism of this system can be found in our previous work [2].This work mainly focused on the distributions of binary particles in the system under variable conditions.First, the particle phases were regarded as fluids and the Eulerian-Eulerian model was developed coupled with kinetic theory of granular flow, which contained three phases, namely gas, sand and oxygen carrier.The parameters of sand and the OC particles are chosen as same as ref.[2].The gas phase was employed as air.The geometry parameters were employed same as the experimental setup, where the diameters of GR, RR and AR were 50 mm, 34 mm and 530 mm while the heights were 500 mm, 6500 mm and 600 mm.Considering the computation complexity and accuracy, a medium grid was chosen for the following simulation works.Then, the simulations were conducted under variable conditions.The gas amount in RR was changed, which were 20.38, 22.32, 24.26, 26.20 and 28.14 m 3 /h.Under these conditions, the flow behaviours of gas and sand particle in GR and the flow mechanisms of gas and oxygen carrier were investigated.Based on the simulation results, the distributions of the sand in GR and oxygen carrier in RR were obtained.The nonuniformity of particle was described using the standard deviation of solid fraction, σp.The variation of σp was further fitted as the function of Nr and axial position.Results showed that the σp decreased with the height of the RR.The σp near OC return spot was largest in each test.The increase of the gas amount would cause the decrease of the σp due to its sufficient fluidizing capability.In the well-developed section of RR, the σp kept near constant.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".