Multi-performance analyses and design optimisation of hydro-pneumatic suspension system for an articulated frame-steered vehicle
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study investigates the coupled ride and directional performance characteristics of an articulated frame-steered vehicle (AFSV). A three-dimensional multi-body dynamic model of the vehicle is formulated integrating the hydro-mechanical frame steering and hydro-pneumatic suspension (HPS) systems. The model parameters are obtained from field-measured data acquired for an unsuspended AFSV prototype and a validated scaled HPS model. The HPS is implemented only at the front axle, which supports the driver cabin. The main parameters of the HPS, including the piston area, and flow areas of bleed orifices and check valves, are selected through design sensitivity analyses and optimisation, considering ride vibration, and roll- and yaw-plane stability performance measures. These include the frequency-weighted vertical vibration of the front unit, root-mean-square lateral acceleration during the sustained lateral load transfer ratio period prior to absolute rollover of the rear unit, and yaw-mode oscillation frequency following a lateral perturbation of the vehicle. The results suggested that the implementation of the HPS to the front unit alone could help preserve the directional stability limits compared to the unsuspended prototype vehicle and reduce the ride vibration exposure by nearly 30%. The results of sensitivity analyses revealed that the directional stability performance limits are only slightly affected by the HPS parameters. Further reduction in the ride vibration exposure was attained with the optimal design, irrespective of the payload variations. The vehicle operation at relatively higher speeds, however, would yield greater vibration exposure.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it