Enhancement of the Distribution of a Liquid Sprayed Into a Fluidized Bed
Bibliographic record
Abstract
In the fluid coking process, bitumen and steam are sprayed into a fluidized bed of coke particles. The liquid reacts on the surface of the hot particles to give distillate products, light gases and coke. A good primary particle/liquid mixing in the spray jet is required in order to achieve high yields of valuable products and minimize operability problems due to particles agglomeration or loss of bed fluidity.An Enhanced Solids Entrainment (ESE) device has been proposed to improve the mixing of droplets and particles during injection. It consists of a cylindrical tube mounted co-axially downstream of the spray nozzle. The objective of this study is to develop an effective and convenient non-invasive technique to quantify the improvements in liquid distribution on the particles that results from the use of ESE device.A slug of 30 vol% ethanol in water solution is sprayed into a fluidized bed of sand. The bed is defluidized shortly after the start of the ethanol water injection. Then, the gas-solid contacting pattern is changed to fixed bed, with downward airflow. The evaporation rate can be obtained from the measured concentration of ethanol in the gaseous effluent. The evaporation rate depends on the wetted area that is exposed to the gas. Good primary dispersion of the liquid on particles yields a large exposed wetted area and, hence, a high evaporation rate. A model is used to estimate the distribution of liquid on the particles from the measured evaporation rate.The experimental results show that the ESE device produces a more uniform primary liquid distribution on the particles, increasing by 7 to 21 % the mass of solids contacted by the injected liquid.
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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".