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Record W2804154536 · doi:10.22215/etd/2017-11759

Experimental Validation of a Time to Instability Theory for Viscoelastic Rings

2017· dissertation· en· W2804154536 on OpenAlexaff
Eugene Lee

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsCarleton University
Fundersnot available
KeywordsViscoelasticityInstabilityRange (aeronautics)Stability (learning theory)MechanicsMaterials scienceStructural engineeringMathematicsComputer scienceEngineeringPhysicsComposite material

Abstract

fetched live from OpenAlex

A novel method of estimation of time to instability of viscoelastic structures has been developed by Dr. C. G. Merrett and has been applied to rings.This theory has applications to the nuclear industry as once the stability of viscoelastic rings is understood, the theory can be expanded to predict the stability of viscoelastic helical coils, which are found in the CANDU nuclear reactor as tight fitting spacers.The theory takes the elastic mechanics of a ring with a uniform pressure load, changes this pressure load to a two point load, applies the elastic-viscoelastic correspondence principle, and then uses Drozdov and Kolmanovskii's stability theory to estimate service life.A computer code using this theory plots the service life of a ring versus viscoelasticity and load.The author would like to thank the following people, in no particular order, for their assistance in the completion of this project:• Dr. C. G.

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.007
GPT teacher head0.271
Teacher spread0.264 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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