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Design, Manufacturing, and Testing of a Metallic Fuselage Panel Incorporating New Alloys and Environmentally Friendly Technologies

2024· article· en· W4392749163 on OpenAlexaff
Alexandra Karanika, Evangelos Carelas, Egoitz Aldanondo, Snir Idel, Alexander Abramoivich, M. van der Geest, Peter Visser

Bibliographic record

VenueJournal of Physics Conference Series · 2024
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsAkzoNobel (Canada)
Fundersnot available
KeywordsEnvironmentally friendlyFuselageManufacturing engineeringEngineeringMaterials scienceMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Within the ecoTECH project, a new fuselage section was designed based on an existing business jet panel, aiming to incorporate innovative technologies and environmentally friendly approaches. The Metallic Fuselage Panel Demonstrator developed in this project integrates the most promising technologies previously developed in the areas of manufacturing methods, including mechanical milling and friction stir welding, as well as surface treatments such as sol-gel and thin film sulphuric acid anodizing, along with a Chrome-free primer applied on a new Al-Cu-Li alloy structure. Two types of full-scale testing were performed to mature the newly developed technologies and assess the performance of the demonstrator. The first was a Static Full-Scale Test Demonstrator, designed and manufactured to undergo static full-scale testing. This testing evaluated the structural integrity and performance of the panel under various load conditions, representative of an operational aircraft, including compression, shear, pressure, tension, and combinations of these forces. The second type of testing conducted concerned endurance. Similar to the static test demonstrator, this demonstrator was subjected to fatigue to assess its durability and long-term performance by simulating representative flight loading spectrum of a business jet aircraft and providing valuable insights into the panel’s ability to withstand prolonged operational conditions. The successful completion of these phases in the ecoTECH project represents a significant milestone, demonstrating the effective integration of innovative manufacturing methods and environmentally friendly surface treatments for new aluminum alloys in the development of innovative environmentally friendly technologies. The project’s outcomes contribute to the advancement of sustainable and efficient technologies in the aerospace industry, providing a foundation for the future development of aircraft structures with improved performance, durability, and reduced environmental impact.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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)0.0010.001

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 head0.031
GPT teacher head0.201
Teacher spread0.170 · 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 designBench or experimental
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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