Numerical and experimental analyses of anti‐fouling and heat transfer in the heat exchanger with circulating fluidized bed
Bibliographic record
Abstract
Abstract Fluidized bed type heat exchangers are known to increase the heat transfer and prevent the fouling. For proper design of circulating fluidized bed heat exchanger it is important to know the effect of design and operating parameters on the bed to the wall heat transfer coefficient. The numerical analysis by using CFX 11.0 commercial code was done for proper design of the heat exchanger. The present experimental studies were also conducted to investigate the effects of circulating solid particles on the characteristics of fluid flow, heat transfer, and cleaning effect in the fluidized bed vertical shell and tube type heat exchanger with counterflow, at which a variety of solid particles such as glass (3 mmØ), aluminum (2–3 mmØ), steel (2–2.5 mmØ), copper (2.5 mmØ), and sand (2–4 mmØ) were used in the fluidized bed with a smooth tube. Seven different solid particles have the same volume, and the effects of various parameters such as water flow rates, particle diameter, materials, and geometry were investigated. The present experimental and numerical results showed that the flow velocity range for collision of particles to the tube wall was higher with heavier density solid particles, and the increase in heat transfer was in the order of sand, copper, steel, aluminum, and glass. This behaviour might be attributed to the parameters such as surface roughness or particle heat capacity. Fouling examination using 25,500 ppm of ferric oxide (Fe 2 O 3 ) revealed that the tube inside wall is cleaned by a mild and continuous scouring action of fluidized solid particles. The fluidized solid particles not only keep the surface clean, but they also breakup the boundary layer improving the heat transfer coefficient even at low‐fluid velocities.
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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".