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Record W2334994701 · doi:10.14510/39ara2015.3916

Optimization of Engine Model Parameters Gain and Time Constant for the Cessna Citation X Business Aircraft Engine

2015· article· en· W2334994701 on OpenAlexafffundabout
Ruxandra Mihaela Botez, Julian Anthony, Clementa Hamel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConstant (computer programming)TurbopropAerospace engineeringAero engineAutomotive engineeringComputer scienceMechanical engineeringEngineeringPhysicsMaterials science

Abstract

fetched live from OpenAlex

The Research Aircraft Flight Simulator was designed and manufactured by CAE Inc., which is a very well known internationally Aerospace Company in Aircraft Modeling and Simulation Technologies. This simulator was designed following specific requirements of the Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity LARCASE team at ETS in Montreal with the aim to be used for research purposes. The authors are the members of the team. This simulator is equipped with a Flight Dynamics Level D open source code, thus it will be used as a Flight Certified Bench Test with the idea to validate Flight Dynamics Models new codes and methodologies. The Cessna Citation X is the fastest today business aircraft available on the market. However, its engine model is unavailable. For this reason, the authors used this simulator in order to obtain, validate and optimize the main parameters of the engine model such as the time constant and gain variations with altitudes and Mach numbers.

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)0.000
metaresearch head score (Gemma)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.209
Teacher spread0.191 · 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
GenreMethods

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
Published2015
Admission routes3
Has abstractyes

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