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Record W2037923462 · doi:10.1063/1.2763955

Flow-induced instability of double-walled carbon nanotubes based on an elastic shell model

2007· article· en· W2037923462 on OpenAlexaff
Y. Yan, Xiaoqiao He, L. X. ZHANG, Quan Wang

Bibliographic record

VenueJournal of Applied Physics · 2007
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of Manitoba
FundersUniversity of Hong KongNational Natural Science Foundation of ChinaCity University of Hong Kong
KeywordsInstabilityCarbon nanotubeShell (structure)van der Waals forceMechanicsRADIUSMaterials scienceFlow (mathematics)Flow velocityShear flowPhysicsNanotechnologyComposite material

Abstract

fetched live from OpenAlex

Double-walled carbon nanotubes (DWCNTs) are modeled based on Donnell’s shell theory, and flow-induced instability that is induced when pressure-driven fluid goes through the inner tube at a steady flow velocity is studied. The van der Waals (vdW) interaction between the inner and outer walls is taken into account in the modeling. The numerical simulations show that the vdW interaction has significant effects on the flow-induced instability of DWCNTs. The critical flow velocities and loss of stability are closely related to the ratio of the length to the outer radius. Donnell’s shell model for carbon nanotubes (CNTs) is preferred in simulations because it takes into account the shear effects in the walls. A comparison between the CNTs that are based on a Eulerian beam model and those that are based on Donnell’s shell model shows that when the 50-nm-radius tube length is shorter than 10 μm, the comparative errors between the Eulerian beam and Donnell’s shell models are greatly increased.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.265
Teacher spread0.242 · 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 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

Citations47
Published2007
Admission routes1
Has abstractyes

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