Tank Shape Optimization for Enhancement of Roll Stability of Partially Filled Tank Vehicles in Steady Turning
Bibliographic record
Abstract
Abstract A generic tank cross-section is proposed to describe the geometry of road tanks used in transportation of bulk liquids, and to explore optimal tank geometry for enhancement of roll stability limits of partially-filled tank vehicles. Two different constrained optimization functions are formulated to minimize the lateral load shift with prescribed cross-sectional c.g. height, and the liquid load shift and c.g. height simultaneously, subject to constraints imposed on the total capacity, overall width and height, and perimeter. Two optimal tank cross-sections are proposed to achieve minimal overturning moments corresponding to medium and high fill ranges. A static roll plane model of the partially-filled generic tank is developed to study the performance potentials of the optimal tanks in terms of translation of the cargo c.g. within the tanks under various fill volumes and vehicle lateral acceleration, which are then compared with those of the conventional circular and modified-oval cross-sectional tanks. The performance potentials of the proposed optimal tanks are further explored in terms of rollover threshold lateral acceleration limit of a partially-filled articulated tank vehicle combination as a function of the fill volume, using a static roll model of the tank vehicle realized by integration of the steady-state roll plane model of the partially-filled generic tank with that of the vehicle. The results reveal that the magnitude of rollover threshold of the 40–70% filled vehicle with the proposed optimal tank geometry is approximately 10% higher than that with a circular cross-sectional tank, and 13–25% higher than that with a modified-oval tank.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".