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Record W2599525898

Improved Real-time Helicopter Flight Dynamics Modelling

2015· dissertation· en· W2599525898 on OpenAlexaboutno aff
Bruce Haycock

Bibliographic record

VenueTSpace (University of Toronto) · 2015
Typedissertation
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsnot available
Fundersnot available
KeywordsFlight dynamicsAerospace engineeringAeronauticsDynamics (music)Flight simulatorComputer scienceEngineeringAerodynamicsPhysics
DOInot available

Abstract

fetched live from OpenAlex

The University of Toronto Institute for Aerospace Studies has a number of previously developed real-time helicopter models for piloted simulations. An area of concern with physics-based helicopter models is that they often have an inaccurate off-axis response to cyclic control inputs compared to flight test data. To explain the cause of this problem, several theories have been put forth in the literature concerning which aspects are modelled incorrectly or not at all, including blade elasticity, rotor wake distortion and curvature, and unsteady aerodynamic effects. In this thesis these modelling improvements were implemented and their effectiveness evaluated. To include blade elasticity, a rotor model was developed using a Ritz expansion approach with constrained elastic modes. The effect of including these features on the on-axis and off-axis response of the UTIAS helicopter models was examined. The various improvements were successful in altering the off-axis response, with notable improvements in some areas, without disrupting the on-axis response. In some conditions, the magnitude of change due to flexibility was greater than differences noted due to dynamic wake distortion or unsteady aerodynamics. The best results were obtained when blade flexibility and wake distortion were used together, which is also the most physically accurate model. The impact of these changes was also evaluated from a pilot-in-the-loop perspective, quantifying the perceived changes using simulation fidelity ratings. Since this is a newly developed metric, the simulator was first evaluated using the original baseline vehicle models. Through this process, experience could be gained in the usage of the fidelity rating scale, while also examining what effect changes to the dynamics had on the overall simulator fidelity rating obtained. While an improved match to flight test data was found to lead to a higher rated fidelity, there was a limit to how high these improvements could increase the fidelity rating. A number of the possible contributors to the ratings achieved were further explored, which for the UTIAS Flight Research Simulator primarily include the motion system fidelity and the collimated stereoscopic visual environment.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.205
Teacher spread0.199 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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