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Record W4401980998 · doi:10.18280/mmep.110820

Structural and Stress Analysis of NACA0012 Wing Using SolidWorks

2024· article· en· W4401980998 on OpenAlexvenueno aff
S NAEEM

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2024
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsWingStress (linguistics)Structural engineeringComputer scienceAeronauticsEngineeringLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

The aircraft wing is a critical component that enables flight and enhances safety and stability.Its design and function are critical considerations in the overall performance and safety of an aircraft.This paper aims to focus on the design of the aircraft wing structure for its importance.SolidWorks-2018 program was used to model the system of the wing parts, which consists of seven ribs and two spars and airfoil NACA 0012 was used and aluminum alloy T7075 as a material for the structure of the aircraft wing and its surface.The generated loads were projected on it obtained using the Vortex Lattice method when dividing it into (8, 16 and 24) panels to extract the amount of stress, strain and deformation to which the wing is exposed.The analyses conducted on the proposed wing showed that the wing structure is acceptable in design because of its lightweight, weighing approximately 5556.98 grams, and safe, as the stress resulting from the numerical analysis under the influence of the aerodynamic force is less than the yield strength of the structural material.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.214
Teacher spread0.195 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractno

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