Effects of Entrapped Gas within the Fluid on the Stiffness and Damping Characteristics of a Hydro-Pneumatic Suspension Strut
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">This study is aimed at characterizing the nonlinear stiffness and damping properties of a simple and low cost design of a hydro-pneumatic suspension (HPS) that permits entrapment of gas into the hydraulic fluid. The mixing of gas into the oil yields highly complex variations in the bulk modulus, density and viscosity of the hydraulic fluid, and the effective gas pressure, which are generally neglected. The pseudo-static and dynamic properties of the HPS strut were investigated experimentally and analytically. Laboratory tests were conducted to measure responses in terms of total force and fluid pressures within each chamber under harmonic excitations and nearly steady temperature. The measured data revealed gradual entrapment of gas in the hydraulic fluid until the mean pressure saturated at about 84% of the initial pressure, suggesting considerably reduced effective bulk modulus and density of the hydraulic fluid. An analytical model of the HPS strut was formulated considering polytropic change in the gas state and increased fluid compressibility due to entrapped air. Both the measured data and the model results showed progressively hardening stiffness of gas during compression, while the damping effect attributed to fluid flows between different chambers was higher during strut rebound. The results further suggested that 20% decrease in fluid density and effective bulk modulus will result in about 18% decrease in the equivalent damping coefficient and 2% decrease in the equivalent stiffness. The reduction in mean strut pressure would also yield relatively higher static deflection of the HPS strut, which could necessitate an additional height adjustment mechanism.</div></div>
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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 | 0.001 | 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 | 0.001 | 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 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".