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Record W4283833690 · doi:10.18280/mmep.090323

Sweep Angles Influence on the Aerodynamic Characteristics of NACA 2412 Wing with Supersonic Flow

2022· article· en· W4283833690 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2022
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsnot available
Fundersnot available
KeywordsAngle of attackWingSwept wingAerodynamicsLift coefficientComputational fluid dynamicsSupersonic speedDragWing twistMechanicsLift-to-drag ratioAerospace engineeringDrag coefficientLift (data mining)Wing loadingReynolds numberPhysicsComputer scienceEngineeringTurbulence

Abstract

fetched live from OpenAlex

A sweep process of a wing is very useful technique to enhance an aircraft performance especially the aircraft which fly in the sonic and supersonic areas. In this research, the influence of swept wing on aerodynamic characteristics generation of aircraft at supersonic speeds has been studied and analyzed using CFD technique. The 3D wing model analyzed and presented in this paper of NACA 2412 profile. The governing equations such as continuity, Energy Equation, and Reynolds Averaging Never-Stokes were solved in conjunction with an analysis of dynamic meshing technique to predict the aerodynamic characteristics and pressure distribution for a wing with a sweep angle ranging from 0° to 60° and a wide range of angle of attack (AOA). In conclusion, depending on the analysis result, increasing of sweep angle can increase the ratio of lift to drag coefficient by about 15%. Moreover, the sweep angle tends to change the load distribution on wing span. Generally, the swept wing has good performance coefficient through the designing an aircraft envelope by optimizing the sweep to get an optimum value of lift/drag ratio. The efficacy and authenticity of the CFD simulations model are shown by comparing the aerodynamic properties findings from the most recent wind tunnel test.

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 score0.343
Threshold uncertainty score0.576

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 head0.008
GPT teacher head0.159
Teacher spread0.151 · 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