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Record W2749032356 · doi:10.4271/2017-01-2085

Combination of Experimental and Computational Approaches to A320 Wing Assembly

2017· article· en· W2749032356 on OpenAlexfundno aff
Sergey Lupuleac, Nadezhda Zaitseva, Margarita Petukhova, Julia Shinder, Sergey Berezin, Valeriia Khashba, Elodie Bonhomme

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2017
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsnot available
FundersAlzheimer Society Research ProgramSaint Petersburg State University
KeywordsWingComputer scienceAerospace engineeringAeronauticsEngineering

Abstract

fetched live from OpenAlex

The paper is devoted to the simulation of A320 wing assembly on the base of numerical experiments carried out with the help of ASRP software. The main goal is to find fasteners’ configuration with minimal number of fastening elements that provides closing of admissible initial gaps. However, for considered junction type initial gap field is not known a priori though it should be provided as input data for computations. In order to resolve this problem the methodology of random initial gap generation based on available results of gap measurements is developed along with algorithms for optimization of fasteners' configuration on generated initial gaps. Presented paper illustrates how this methodology allows optimizing assembly process for A320 wing.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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

Citations21
Published2017
Admission routes1
Has abstractyes

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