Straight-line braking dynamic analysis of a partly filled baffled and unbaffled tank truck
Bibliographic record
Abstract
Abstract The straight-line braking performance characteristics of a partly filled tank truck with and without transverse baffles are investigated in the presence of transient fluid slosh within the tank. The dynamic interactions of the floating cargo with the vehicle are evaluated by integrating a dynamic fluid slosh model of the partly filled tank with and without transverse baffles with the seven-degrees-of-freedom pitch plane model of a tridem truck. The dynamic fluid slosh within the tank containing equally spaced four curved single-orifice baffles with flow equalizer is modelled using three-dimensional Navier—Stokes equations coupled with the volume-of-fluid equation and analysed using the FLUENT software. The coupled tank—vehicle model is subsequently analysed to determine the straight-line braking properties for different fill volumes, magnitudes of braking treadle pressure, and road surface adhesion coefficients, while the cargo load is considered to be constant. The results show interactions of the sloshing cargo with the vehicle. A degradation of the braking performance of the partly filled tank truck is evident in the presence of transient fluid slosh, particularly in the absence of baffles. The braking performance, however, is highly dependent upon the fill volume, presence of baffles, and severity of braking input. For a clean-bore tank truck, the stopping distance increases monotonically with decreasing fill volume, while the addition of transverse baffles in general results in considerably shorter stopping distance. The baffled tank truck, however, reveals a relatively shorter stopping distance under an intermediate fill condition (approximately 52.1 per cent), compared with the lower and higher fill volumes. Although the analyses are limited to conventional single-orifice baffles, the proposed coupled vehicle—tank model could serve as an important tool for exploring alternative baffle designs and layouts.
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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 | 0.001 | 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".