MétaCan
Menu
Back to cohort
Record W2618259400 · doi:10.5539/mer.v7n1p44

Kinematics and Internal Dynamics Formulations of the Canis Compressed Air Engine

2017· article· en· W2618259400 on OpenAlexvenueno aff
Ngang Tangie Fru

Bibliographic record

VenueMechanical Engineering Research · 2017
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsnot available
Fundersnot available
KeywordsKinematicsAccelerationDisplacement (psychology)Mechanical engineeringCompressed airConnecting rodComputer scienceAutomotive engineeringMechanicsEngineeringPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

Prior to this paper some study was conducted that resulted to the conceptual design of the Canis Compressed Air Engine. This paper brings out the mathematical design of the Canis Compressed Air engine. It also highlights the study of the kinematic and internal dynamic formula. With the engine components movement likened to an eccentric circular cam, with a radial movement (Ri) and a normal movement component (Di) and a different (di), with the magnitude of the radial movement (Ri) and different (di) considered constant, respectively 4units and 1units, the mathematical formula describing the displacement, velocity and acceleration were verified. This verification, done graphically, ended up with the conclusion that this design of a compressed air engine, complies theoretically with the recommendations of accurate intake and exhaust positioning, smooth running and high efficiency due to absence of backlashing forces during intake. The theoretical internal dynamics analysis further proofs the susceptibility of a perfect intake then explosive expansion and a perfect exhaust for every expansion chamber.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.693
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.318
Teacher spread0.278 · 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 teacher head, 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueMechanical Engineering ResearchSame topicMechanical Engineering and Vibrations ResearchFrench-language works237,207