MétaCan
Menu
Back to cohort

Modelling and Analysis of a Virtual Prototype of a Rotary Machine in MSC.ADAMS

2021· article· en· W3217568231 on OpenAlexaboutno aff
Alžbeta Sapietová, Vladimír Dekýš, Milan Sapieta, A Jastraban, María Luisa Carrió Pastor

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicMechanical and Thermal Properties Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRotor (electric)Angular velocityCritical ionization velocityCenter of gravitySoftwareCritical speedOrbit (dynamics)TrajectoryMechanical engineeringEngineeringStability (learning theory)Aerospace engineeringSimulationComputer scienceControl theory (sociology)MechanicsPhysicsClassical mechanicsOperating system

Abstract

fetched live from OpenAlex

Abstract The article presents an analysis of the virtual model of Laval (Jeffcott) rotor in the software environment MSC.ADAMS. The parameters describing the stability of the rotor operation were monitored and evaluated, i. j. critical angular velocity and trajectory of the rotor center of gravity (orbit). The results were compared with the values measured on the experimental equipment, as well as with the values obtained by analytical calculation. The paper further presents a simulation in which the second critical velocity was reached. The paper further presents a simulation in which the second critical velocity was reached.

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)0.001
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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.015
GPT teacher head0.191
Teacher spread0.176 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueIOP Conference Series Materials Science and EngineeringSame topicMechanical and Thermal Properties AnalysisFrench-language works237,207