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Record W2000429565 · doi:10.1115/imece2006-13961

A Generalized Model of a Class of Interconnected Hydro-Pneumatic Suspensions and Analysis of Pitch Properties

2006· article· en· W2000429565 on OpenAlexaff
Dongpu Cao, Subhash Rakheja, Chun‐Yi Su

Bibliographic record

VenueDesign Engineering and Computers and Information in Engineering, Parts A and B · 2006
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsSuspension (topology)StiffnessFluidicsCoupling (piping)Flexibility (engineering)Structural engineeringEngineeringMechanical engineeringAerospace engineering

Abstract

fetched live from OpenAlex

The static and dynamic properties of pitch-interconnected hydro-pneumatic vehicle suspensions are derived using a generalized analytical model. The suspensions incorporate two compact struts with integrated gas chambers and damping valves within each unit. The struts provide superior flexibility in realizing fluidic couplings, while offering large effective working area. The proposed suspension configurations consist of hydraulic, pneumatic or hybrid fluidic couplings between the front and rear suspension struts. The coupling effects due to different interconnected suspensions are established through the mathematical formulations. A generalized model of the hydro-pneumatic suspensions is developed that could be applied for either the roll or pitch plane of the vehicle, permitting analyses of suspension forces in a very simple manner. The 7-DOF pitch plane model of a heavy vehicle is analyzed to derive the relative vertical and pitch properties of different suspension configurations, in terms of suspension rates, pitch stiffness, bounce and pitch mode damping properties. The results suggest that the use of fluidic interconnections could yield considerable design flexibility and reduced coupling between the bounce and pitch stiffness properties, while the hydraulic and hybrid fluidic couplings offer added flexibility in tuning the bounce and pitch damping characteristics. The influence of load distribution on the bounce and pitch stiffness properties is also explored.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.011
GPT teacher head0.167
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2006
Admission routes1
Has abstractyes

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Same venueDesign Engineering and Computers and Information in Engineering, Parts A and BSame topicHydraulic and Pneumatic SystemsFrench-language works237,207