MétaCan
Menu
Back to cohort
Record W3103738677 · doi:10.22215/etd/2020-14144

Development of a Planar Shipboard Skid-Equipped Rotary-Wing Aircraft Manoeuvring and Securing Simulation

2020· dissertation· en· W3103738677 on OpenAlexaff
Alexander Schock

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsSkid (aerodynamics)AirframeEngineeringLanding gearAerospace engineeringAerodynamicsFinite element methodMarine engineeringInterface (matter)Helicopter rotorRotor (electric)Mechanical engineeringStructural engineering

Abstract

fetched live from OpenAlex

In maritime shipboard operations, the typical `skid-type' landing gear of unmanned aircraft systems constrain mechanical securing and traversing options, and present complex ship-helicopter interface behaviour which must be characterized. The planar case of a dynamic interface package named SRAMSS (Skid-equipped Rotary-wing Aircraft Manoeuvring and Securing Simulation) has been developed. SRAMSS models the aircraft as a mass-coupled rigid airframe and flexible landing gear by integration of dynamic finite element modelling into Kane's method. Oriented ship-aircraft contact dynamics is modelled by a Separation Axis Theorem algorithm. Aerodynamic drag, and rotor blade element models complete the modelling of the embarked aircraft. Verification of SRAMSS confirms the proper implementation of the included models. Preliminary validation of the rotor model against published data indicates the need for refinement. Nevertheless, this work verifies a suitable system formulation methodology for a state-of-the-art fully-spatial dynamic interface simulation package for skid-equipped rotary-wing aircraft.

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 categoriesMeta-epidemiology (narrow)
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 score0.131
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.012
GPT teacher head0.236
Teacher spread0.223 · 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.

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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicReal-time simulation and control systemsFrench-language works237,207