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Record W2966083424 · doi:10.1108/hff-09-2018-0497

Strong fluid–solid interactions with segregated CFD solvers

2019· article· en· W2966083424 on OpenAlexaff
Mathieu Olivier, Olivier Paré-Lambert

Bibliographic record

VenueInternational Journal of Numerical Methods for Heat &amp Fluid Flow · 2019
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSolverComputer scienceComputational fluid dynamicsFlow (mathematics)Overhead (engineering)Context (archaeology)Coupling (piping)Fluid dynamicsScheme (mathematics)TurbulenceMechanicsApplied mathematicsMathematicsPhysicsMechanical engineeringMathematical analysisEngineeringGeology

Abstract

fetched live from OpenAlex

Purpose This paper aims to present a fluid-structure coupling partitioned scheme involving rigid bodies supported by spring-damper systems. This scheme can be used with already existing fluid flow solvers without the need to modify them. Design/methodology/approach The scheme is based on a modified Broyden method. It solves the equations of solid body motion in which the external forces coming from the flow are provided by a segregated flow solver used as a black box. The whole scheme is implicit. Findings The proposed partitioned method is stable even in the ultimate case of very strong fluid–solid interactions involving a massless cylinder oscillating with no structural damping. The overhead associated with the coupling scheme represents an execution time increase by a factor of about 2 to 5, depending on the context. The scheme also has the advantage of being able to incorporate turbulence modeling directly through the flow solver. It has been tested successfully with URANS simulations without wall law, thus involving thin high aspect-ratio cells near the wall. Originality/value Such problems are known to be very difficult to solve and previous studies usually rely on monolithic approaches. To the authors' knowledge, this is the first time a partitioned scheme is used to solve fluid–solid interactions involving massless components.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.254
Threshold uncertainty score0.811

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.018
GPT teacher head0.349
Teacher spread0.331 · 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
GenreMethods

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

Citations8
Published2019
Admission routes1
Has abstractyes

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