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Record W1963690397 · doi:10.1016/j.procir.2014.07.077

Process for Advanced Management and Technologies of Aircraft EOL

2015· article· en· W1963690397 on OpenAlexaffabout
Christian Mascle, Pierre Baptiste, D. Sainte Beuve, Aurore Camelot

Bibliographic record

VenueProcedia CIRP · 2015
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsDispose patternScope (computer science)EngineeringProcess (computing)Work (physics)Systems engineeringManufacturing engineeringRisk analysis (engineering)Waste managementBusinessComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

Different possibilities are available to treat aircraft end-of-life (EOL), each with positive and negative impacts on the 3 spheres of sustainable development. EOL processing includes 4 major steps: decontamination, disassembly of reused or remanufactured parts, dismantling of the remaining carcass, materials recovery and valorization and/or landfill. In this paper, we present general methods to dispose of and/or implement profitable rebirthing processes and a dedicated infrastructure for end-of-life aircraft (real Bombardier CRJ100) and helicopters operated in Canada. This work is critical to help aircraft manufacturers design current and next generation aircraft and to facilitate disposal after use. The scope of this project is well rounded and includes all aspects related to dismantling of an aircraft; from legal, to scientific and engineering. These aspects are studied using both modeling and experimental approaches.

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: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.232
Teacher spread0.218 · 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".

Quick stats

Citations25
Published2015
Admission routes2
Has abstractyes

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Same venueProcedia CIRPSame topicManufacturing Process and OptimizationFrench-language works237,207