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Record W4283829435 · doi:10.5281/zenodo.6801154

Multidisciplinary design of a more electric regional aircraft including certification constraints

2022· paratext· en· W4283829435 on OpenAlexafffund
Marco Fioriti, Thierry Lefèbvre, Pierluigi Della Vecchia, Massimo Mandorino, Susan Liscouët-Hanke, Andrew K. Jeyaraj, G. Donelli, A. Jungo

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typeparatext
Languageen
FieldEnvironmental Science
TopicAdvanced Aircraft Design and Technologies
Canadian institutionsConcordia University
FundersConcordia UniversityEuropean CommissionNatural Sciences and Engineering Research Council of CanadaHorizon 2020 Framework ProgrammeConsortium de Recherche et d’innovation en Aérospatiale au Québec
KeywordsMultidisciplinary approachCertificationAeronauticsComputer scienceSystems engineeringEngineeringPolitical science

Abstract

fetched live from OpenAlex

The use of electrified on-board systems is increasingly more required to reduce aircraft complexity, polluting emissions, and its life cycle cost. However, the more and all-electric aircraft configurations are still uncommon in the civil aviation context and their certifiability has yet to be proven in some aircraft segments. The aim of the present paper is to define a multidisciplinary design problem which includes some disciplines pertaining to the certification domain. In particular, the study is focused on the preliminary design of a 19 passengers small regional turboprop aircraft. Different on-board systems architectures with increasing electrification levels are considered. These architectures imply the use of bleedless technologies including electrified ice protection and environmental control systems. The use of electric actuators for secondary surfaces and landing gear are also considered. The aircraft design, which includes aerodynamic, structural, systems and propulsion domains, is then assessed by some certification disciplines. In particular, minimum performance, external noise and safety assessments are included in the workflow giving some insights on the aircraft certifiability. The results show a reduction of 3% of MTOM and 3% of fuel mass depending on the systems architecture selected. From the certification side, the design has proven to be certifiable and the margins with the certification constraint can be controlled to improve the overall design.

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 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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.690
Threshold uncertainty score1.000

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 studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1980.023

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 head0.074
GPT teacher head0.284
Teacher spread0.210 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2022
Admission routes2
Has abstractyes

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