Numerical investigation of nanofluid heat transfer in the wall cooling panels of an electric arc steelmaking furnace
Bibliographic record
Abstract
Abstract Wall cooling panels are typically a kind of electric arc furnace equipment that has precisely influence on different aspects of the steelmaking process. This investigation employs a CFD method to evaluate the thermal performance of water cooling panels in real operating conditions to validate the numerical method followed by replacing cooling water with Al 2 O 3 /Water nanofluid coolant. The results are revealed that the high rate of receiving heat flux and generated vortexes with low-velocity cores lead to hot spots inducing on bends and elbows. In the operating flow rate, the maximum temperature of the hot-side wall decrease by 14.4% through increasing the nanoparticle concentration up to 5%, where the difference between maximum temperature and average temperature on the hot-side decrease to 12 degrees. According to the results, use of nanofluid coolant is a promising method to fade the hot spots out on the hot-side and gifting a lower and smoother temperature distribution on the panel walls of thereby prolonging the usage period of panels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".