A Performance Study on Structural Parameters of Centre-Axle-Trailer Combinations
Bibliographic record
Abstract
Compared with rigid-trucks, centre-axle-trailer (CAT) combinations significantly improve fuel economy and reduce greenhouse-gas emissions.However, with respect to rigid-trucks, CAT combinations exhibit lower lateral stability at high speeds, and display poorer path-following offtracking (PFOT) at low speeds.This study intends to address these problems.To this end, eigenvalue analysis and simulation were conducted to evaluate the directional performance of CAT combinations considering the variations of typical structure parameters.To coordinate the trace-off between the lateral stability in terms of rearward amplification (RWA) and PFOT of CAT combinations, a CAT design with a variable-length drawbar was proposed.The drawbar length may be altered under different operating conditions, e.g., low-speed curved-path negotiations and high-speed evasive manoeuvres.The proposed variable-length drawbar is feasible in design and cost-effective in implementation.The insightful results derived from this study provide useful guidelines for the design CAT combinations to improved directional performance.
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 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) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".