Numerical Study on the Sloshing Behaviors of Dual Liquid Tanks with Gas Inflow
Bibliographic record
Abstract
The finite volume method (FVM) is used to numerically investigate the sloshing behaviors of dual liquid tanks with gas inflow in this study. The sloshing process of a single liquid tank is simulated to verify the feasibility of the numerical method. Three different inlet boundary conditions are then discussed in order to obtain a reasonable gas flow rate. The sloshing process of a dual liquid tank with the gas inflow is simulated, and the effects of three different factors on the sloshing behaviors are investigated. The results indicate that the overload, flow rate, and filling ratio can affect the peak value of the impact force acting on the tank wall. The impact force is positively proportional to the overload (1G, 3G, or 5G). An increase in flow rate (50 g/s, 1000 g/s, or 5000 g/s) or a decrease in filling ratio (99.52%, 75.64%, or 63.69%) can increase the size and number of bubbles, leading to intensified sloshing behavior and increased impact force.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".