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Record W4295953517 · doi:10.4050/f-0078-2022-1318

Tolerance Relief on Transmissions Castings for Producibility

2022· article· en· W4295953517 on OpenAlexaff
Brad Gimbutis, Griffin Palmer, Justin Beardsley, Holly Quinn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsCastingStiffnessPolygon meshMaterials scienceMechanical engineeringEnhanced Data Rates for GSM EvolutionAutomotive engineeringComputer scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

Helicopter gearbox transmission castings must be designed for adequate strength, adequate stiffness for gear meshes and flight loads, clean-up of all machined surfaces, adequate edge distance for all clamped connections and minimum weight. Castings manufacturers generally request relatively large tolerances due to the nature of the casting processes in the order of +/- 0.100 inch while designers will require casting tolerances in the order of +/- 0.030 inch for cast surfaces. Excess casting material can lead to assembly interferences and excess weight while insufficient material can lead to thin wall conditions, lack of damage repair capability and potential performance issues. This paper describes how skewed (unilateral or unequally disposed) casting tolerances can eliminate casting rejections, eliminate Material Review Board (MRB) delays, eliminate reworks, ensure proper performance, and have negligible impact on weight.

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: Empirical · Consensus signal: none
Teacher disagreement score0.559
Threshold uncertainty score0.383

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 head0.015
GPT teacher head0.219
Teacher spread0.204 · 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
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

Citations0
Published2022
Admission routes1
Has abstractyes

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