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Crashworthiness Design Optimization for an eVTOL Aircraft

2022· article· en· W4317383352 on OpenAlexaff
Menglong Ding, Anhuan Xie, Shiqiang Zhu, Wei Song, Jiandong Cai, Xufei Yan, Pengyu Zhao, Jason Gu, Yanyan Zhang

Bibliographic record

Venue2022 IEEE International Conference on Robotics and Biomimetics (ROBIO) · 2022
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCrashworthinessTakeoffCockpitLanding gearAutomotive engineeringEngineeringTakeoff and landingRange (aeronautics)CrashSkid (aerodynamics)Aerospace engineeringStructural engineeringComputer scienceFinite element method

Abstract

fetched live from OpenAlex

The emergence of electric Vertical Takeoff and Landing (eVTOL) aircraft makes cheap, quiet and reliable short-range flights possible. As a manned aircraft, eVTOL's occupant protection capability is critical and its crashworthiness must be improved via optimization of energy absorption design for structures. This study aims to evaluate the crashworthiness of composite components and the entire eVTOL structure within the design space via the building-block approach. A variety of designs for the skid landing gear, energy absorber, structures in the cockpit and the combination of them were estimated by using the numerical method. The results show a tremendous reduction in occupant injury risk with the optimization of the skid landing gear, energy absorber and the entire eVTOL structure. This work provides a preliminary optimization design and evaluation methodology of crashworthiness for an eVTOL.

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 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 score0.956
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.268
Teacher spread0.224 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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