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Record W2268571332 · doi:10.4271/2000-01-0833

Kinematic Solution and Force Layout of a Roller Pump with Internal Outlets

2000· article· en· W2268571332 on OpenAlexaff
Nadezhda Zhurba, William L. Cleghorn

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2000
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsKinematicsMechanical engineeringInternal forcesComputer scienceEngineering drawingEngineeringStructural engineeringPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

The article presents a theoretical analysis of a roller pump design and a summary of the experiments. The pump is to provide high pressure for transmission, accessory drive, and other applications. A theoretical model was built to simulate the motion of the rollers and optimize the design. An experiment was conducted to prove the simulation. The mathematical model was built within constraints of rigid body mechanics. Comprehensive kinematic and force analysis was done through differential equations of motion. Obtained quantitative relationships include, on one hand, pump geometry, speed of rotation, and discharge/suction oil pressure, and, on the other hand, torque, dynamic interaction of relatively moving parts, and kinematic parameters of the roller. The model includes dissipate forces to account for hydraulic effects. Modeling these forces is beyond mechanics of solid body and is not considered at this initial stage of research. The simulation used matrix algebra, recursive methods of solving non-linear system of equations, ordinary differential equations. Calculations were done by means of MathCad7 Professional software in a MathConnex frame. Tests were conducted on a hydraulic pump test stand with capabilities to set and measure speed, pressure, torque, flow, and temperature. The research showed that a mathematical model built on fundamental scientific basis and strengthened with modern computer tools is valid for explaining available experimental facts; therefore, it may be used for optimizing geometry the model is flexible: new components, such as those representing hydrodynamic effects, may be easily added for better approximation both calculations and experiments revealed some drawbacks of the design; nevertheless, further development is feasible.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0150.001

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 head0.008
GPT teacher head0.211
Teacher spread0.203 · 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 designBench or experimental
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

Citations2
Published2000
Admission routes1
Has abstractyes

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