Pressure-Dependent Nonlinearities of a Compact Hydropneumatic Strut with Integrated Gas–Oil Chamber
Bibliographic record
Abstract
<div>Hydropneumatic Struts (HPS) are widely implemented in automobile, aerospace, and construction industries, mainly for the purpose of vibration and shock absorption. The HPS design with integrated gas–oil chamber is relatively more compact and robust, while mixing gas and oil inside the HPS generates gas–oil emulsion and more nonlinearities. This study formulated a nonlinear analytical model of the compact HPS with gas–oil emulsion, considering the real gas law and pressure-dependent LuGre friction model. The polytropic version of the van der Waals (vdW) method for real gas is applied to represent the thermodynamic behavior of nitrogen. The experimental data were collected at a near temperature of 30°C with three charging pressures under excitations in the frequency range of 0.5–6 Hz, considering two flow connection configurations between chambers as one- and two-bleed orifice. The nonlinear behavior of the gas volume fraction of the emulsion was identified based on peak strut velocity and charge pressure. Discharge coefficients of bleed and check valves were determined as a function of the instantaneous pressure difference between chambers. The parameters of the pressure-dependent LuGre model, such as the stiction force and Coulomb force apart from stiffness and damping coefficient of bristle deflection, were also investigated considering the effect of pressure variation. Compared to the generally used ideal gas and models, the proposed model considerably improved the prediction accuracy of the total force and pressures of HPS, with normalized root-mean-square deviations of about 8%.</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 | 0.000 | 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) | 0.000 | 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".