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Record W3167251259 · doi:10.1017/aer.2021.29

Wing component allocation for a morphing variable span of tapered wing using finite element method and topology optimisation – application to the UAS-S4

2021· article· en· W3167251259 on OpenAlexaff
Mohamed Elelwi, T. P. Calvet, Ruxandra Mihaela Botez, T. M. Dao

Bibliographic record

VenueThe Aeronautical Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicTopology Optimization in Engineering
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsWingspanWingStructural engineeringMorphingFinite element methodTopology optimizationTopology (electrical circuits)EngineeringStiffnessComponent (thermodynamics)Computer science

Abstract

fetched live from OpenAlex

Abstract This work presents the Topology Optimisation of the Morphing Variable Span of Tapered Wing (MVSTW) using a finite element method. This topology optimisation aims to assess the feasibility of internal wing components such as ribs, spars and other structural components. This innovative approach is proposed for the telescopic mechanism of the MVSTW, which includes the sliding of the telescopically extended wing into the fixed wing segment. The optimisation is performed using the tools within ANSYS Mechanical, which allows the solving of topology optimisation problems. This study aims to minimise overall structural compliance and maximise stiffness to enhance structural performance, and thus to meet the structural integrity requirements of the MVSTW. The study evaluates the maximum displacements, stress and strain parameters of the optimised variable span morphing wing in comparison with those of the original wing. The optimised wing analyses are conducted on four wingspan extensions, that is, 0%, 25%, 50% and 75%, of the original wingspan, and for different flight speeds to include all flight phases (17, 34, 51 and 68m/s, respectively). Topology optimisation is carried out on the solid wing built with aluminium alloy 2024-T3 to distribute the wing components within the fixed and moving segments. The results show that the fixed and moving wing segments must be designed with two spar configurations, and seven ribs with their support elements in the high-strain area. The fixed and moving wing segments’ structural weight values were reduced to 16.3 and 10.3kg from 112 to 45kg, respectively. The optimised MVSTW was tested using different mechanical parameters such as strains, displacements and von Misses stresses. The results obtained from the optimised variable span morphing wing show the optimal mechanical behaviour and the structural wing integrity needed to achieve the multi-flight missions.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.021
GPT teacher head0.276
Teacher spread0.255 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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