Analysis of transient fluid slosh in partly-filled tanks with and without baffles: Part 1 – model validation
Bibliographic record
Abstract
Fluid slosh in partly-filled tanks is modelled as a two-phase flow, and solved using a Navier-Stokes (NS) solver, while the interface of two fluids is tracked using the VOF technique. The fluid slosh in cleanbore and baffled scale model tanks was further characterised in the laboratory, under different fill levels and excitations. The validity of the slosh model, reduced to the scale model tank, was evaluated using the measured data in terms of fundamental slosh frequency, and transient and steady-state slosh forces and moments over a wide range of conditions such as the tank configuration, fill level and acceleration excitation. The model results showed reasonably good agreements with the measured data, irrespective of tank configuration, fill level and the acceleration excitation. It is concluded that the dynamic fluid slosh model can effectively predict the forces and moments associated with 3-D fluid slosh observed under lateral or longitudinal excitations. The fluid slosh model may thus be integrated to the vehicle model to investigate partly-filled tank vehicle responses and the role of baffles. The slosh forces and moments responses of a full-size tank model were subsequently evaluated using FLUENT software.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".