The ash deposition and structure characteristics for radiant syngas cooler based on the fluid‐thermal‐structure method using numerical simulation
Bibliographic record
Abstract
Abstract The radiant syngas cooler (RSC) has the potential to significantly enhance energy efficiency as a critical heat recovery device in entrained‐flow coal gasification technology. The dimensions of the RSC have a direct impact on the flow and heat transfer processes. In this study, an analysis was conducted to evaluate the heat transfer, ash deposition, and thermal structural deformation characteristics based on the fluid‐thermal‐structure interaction method of the RSC. The simulation results exhibit a high degree of correlation with the industrial data. The results indicate that the increase in length‐diameter ratios decreases the area of the recirculation zone. Ash deposition thickness increases with the increase of length–diameter ratios. A maximum ash deposition thickness of 15.2 mm while the length‐diameter ratio is 9. The effect of ash deposition is amplified with an increase in length–diameter ratios on heat transfer. The thermal deformation of top and bottom structures is observed to increase with an increase in length–diameter ratios without ash deposition while decreasing with ash deposition. For the optimized RSC structure, an increase in inlet temperature and load results in a corresponding increase in ash layer thickness, while the effect on thermal deformation is limited. The current results can serve as a reference for the integral structural optimal design of industrial RSC.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".