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Record W2059400134 · doi:10.5555/1400549.1400663

Modelling and simulation of skid-equipped shipboard rotorcraft

2008· article· en· W2059400134 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSpring Simulation Multiconference · 2008
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsCurtiss-Wright (Canada)York UniversityCarleton University
Fundersnot available
KeywordsSkid (aerodynamics)Landing gearEngineeringDeckNonlinear systemMarine engineeringComputer scienceAerospace engineeringAutomotive engineeringMechanical engineeringStructural engineering

Abstract

fetched live from OpenAlex

Mathematical modelling and computer simulation has proven to be the tool of choice for supporting the development and operation of shipboard aircraft securing and handling equipment. While other alternatives have been used for specific phases and aspects of operation, the variety of nonlinear effects present and range of analysis types that are required strongly support transient time-domain simulation as the most versatile option. The DYNAFACE® simulation program has been developed over the past fifteen years and is widely used for this purpose, particularly for the analysis of conventional shipboard aircraft designed with wheeled landing gears. Increasingly, a requirement has emerged for the ability to model shipboard aircraft having skid landing gear -- both due to occasional use of land-based aircraft aboard ships and for supporting the design and operation of ship-based UAVs that are often fitted with skid landing gear. This paper describes in detail for the first time recent mathematical modelling resulting in the extension of DYNAFACE® capabilities to include the modelling of skid-equipped rotorcraft both using a fast linear stiffness modelling approach for the gear and using a more-general nonlinear finite element structural modelling approach. In both cases, an efficient skid/deck interface model is used. The two modelling options provide versatility in the type of analysis that can be performed. Sample results from a typical analysis are also presented and discussed.

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.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.857

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 head0.038
GPT teacher head0.255
Teacher spread0.217 · 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