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Record W3118888785 · doi:10.2514/6.2021-0620

Topology Optimization of a Section of a Morphing Serpentine Aircraft Inlet

2021· article· en· W3118888785 on OpenAlex
Evan M. Munroe, Rubens Bohrer, Wajid A. Chishty, Il Yong Kim

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIAA Scitech 2021 Forum · 2021
Typearticle
Languageen
FieldEngineering
TopicTopology Optimization in Engineering
Canadian institutionsNational Research Council CanadaQueen's University
Fundersnot available
KeywordsMorphingTopology optimizationAirframeAerodynamicsAerospace engineeringInletComputer scienceShape optimizationMechanical engineeringPropulsionEngineeringTopology (electrical circuits)Structural engineeringFinite element method

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2021-0620.vid The applicability of morphing structures for airframe design is well documented, as aircraft surfaces are sensitive to flight conditions and environmental factors. This becomes a critical factor in the design of airframes with internally mounted propulsion systems. Such designs necessitate the use of a serpentine inlet, the optimal shape of which is dependent on flight conditions. This work focusses on the structural optimization of a section of a serpentine aircraft inlet capable of morphing. The trade-offs between morphing ability and structural performance are of key interest, and are explored in this study. As a structure becomes more compliant to accommodate a change of shape, it loses structural stiffness. A topology optimization algorithm was written to generate a Pareto Frontier of optimal designs for this problem. The scope of this work is limited to a small section of a specific serpentine inlet design for which aerodynamic shape optimization for different flight conditions has already been conducted.

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: Methods · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score0.681

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)0.0010.000

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 head0.005
GPT teacher head0.205
Teacher spread0.200 · 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