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Record W2030865919 · doi:10.1002/nme.2670

Immersed particle method for fluid–structure interaction

2009· article· en· W2030865919 on OpenAlexaff
Timon Rabczuk, Robert Gracie, Jeong‐Hoon Song, Ted Belytschko

Bibliographic record

VenueInternational Journal for Numerical Methods in Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsUniversity of Waterloo
FundersOffice of Naval Research
KeywordsClassification of discontinuitiesFluid–structure interactionCoupling (piping)MechanicsParticle (ecology)Particle methodFluid dynamicsSimple (philosophy)Discrete element methodPartition (number theory)Classical mechanicsMaterials sciencePhysicsStructural engineeringMathematicsEngineeringFinite element methodGeologyMathematical analysisComposite material

Abstract

fetched live from OpenAlex

Abstract A method for treating fluid–structure interaction of fracturing structures under impulsive loads is described. The coupling method is simple and does not require any modifications when the structure fails and allows fluid to flow through openings between crack surfaces. Both the fluid and the structure are treated by meshfree methods. For the structure, a Kirchhoff–Love shell theory is adopted and the cracks are treated by introducing either discrete (cracking particle method) or continuous (partition of unity‐based method) discontinuities into the approximation. Coupling is realized by a master–slave scheme where the structure is slave to the fluid. The method is aimed at problems with high‐pressure and low‐velocity fluids, and is illustrated by the simulation of three problems involving fracturing cylindrical shells coupled with fluids. Copyright © 2009 John Wiley & Sons, Ltd.

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)0.002
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 score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.020
GPT teacher head0.396
Teacher spread0.377 · 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

Citations403
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal for Numerical Methods in EngineeringSame topicFluid Dynamics Simulations and InteractionsFrench-language works237,207