MétaCan
Menu
Back to cohort
Record W2014179348 · doi:10.5539/mas.v6n6p18

A Study of Non-linear Dynamic Aerodynamic Behaviour of a Specialised Delta Wing

2012· article· en· W2014179348 on OpenAlexvenueno aff
Christopher Pevitt, Firoz Alam

Bibliographic record

VenueModern Applied Science · 2012
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAerodynamicsComputational fluid dynamicsDelta wingComputer scienceWingWind tunnelSoftwareFlow (mathematics)Range (aeronautics)Angle of attackSimulationDynamic simulationProcess (computing)Aerospace engineeringMechanicsEngineeringPhysics

Abstract

fetched live from OpenAlex

The objective of this paper was to model the stability and control derivatives using Computational Fluid Dynamics (CFD). This would provide a more reliable tool in the development of aircraft. This process could reduce the reliance on wind tunnel results with a consequent reduction in development costs. The test model used for this paper was a specialised delta wing configuration. The study was undertaken by comparing simulation parameters and determining their effects on the flow characteristics. The simulation was undertaken using internal meshing software, the flow simulation software TAU and the graphical interface Tecplot. Results showed that a single CFD model could not be used for the prediction of aerodynamic behaviour under the full range of angle of attack (0° to 25°). However the surface mesh refinement and optimisation of simulation parameters allowed for a better prediction at lower angle of attack (0° to 15°). The dynamic simulation showed that flow characteristics were better captured for higher pitching frequencies. Overall the study will assist the progress of future studies.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.253
Teacher spread0.241 · 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
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

Citations1
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueModern Applied ScienceSame topicComputational Fluid Dynamics and AerodynamicsFrench-language works237,207