Numerical Simulation of Thermal Storage Tank with Middle Baffles Distributions
Bibliographic record
Abstract
A numerical investigation into the influence of baffle placement on thermal stratification within a vertical cylindrical cold-water tank is conducted.The tank, sporting a diameter of 400 mm and a height of 1000 mm, incorporates inlet and outlet ports of equal diameter (17.39 mm).The baffles, integral to this study, are of 200 mm in length and 2 mm in thickness.The study leverages computational methodologies to decipher the equations that govern heat transfer and fluid flow within a baffle-integrated tank.The tank commences with an initial water temperature of 4.4℃, and an inflow of water at 13.3℃, from the upper left side.Validation of the adopted tests is sought through experimental data available in extant literature.The abstract delves into the impact of baffle number and positioning on a multitude of elements-thermocline temperature, streamline creation, vortex formation, velocity vectors, Stratification Number, and Richardson Number-across varied cases during the discharging phase.The introduction of one or two baffles exerts a marginal effect on temperature distribution contours.However, a third baffle accentuates this impact, expanding the hot-cold interface with a pronounced penetration effect within the tank.Interestingly, the influence of three baffles on temperature distribution contours diminishes at a discharging time of 2173.4 s.This study provides insight into the nuanced role of baffles within thermal storage tanks, elucidating key considerations for their optimal placement and number.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".