Sweep Angles Influence on the Aerodynamic Characteristics of NACA 2412 Wing with Supersonic Flow
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".