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Record W4229442274 · doi:10.2218/marine2021.6804

Novel Modeling Methodology of the Deep-water Flexible Riser with the Slug-flow

2022· article· en· W4229442274 on OpenAlexaff
HANZE YU, YONGHE XIE, GANGQIANG LI, Lijun Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsYork University
Fundersnot available
KeywordsSlugSlug flowFlow (mathematics)Environmental sciencePetroleum engineeringMarine engineeringComputer scienceGeologyMechanicsEngineeringTwo-phase flowPhysics

Abstract

fetched live from OpenAlex

Slug flow, being the mixture of oil, gas and water, can increase the dynamics and structural response of a riser in internal fluid transportation due to the variation of slug flow's force caused by the time-space varying density.This paper presents a high-fidelity model of a flexible deep-water riser based on the absolute nodal coordinate formulation with slug flow in the arbitrary Lagrangian-Eulerian description.In the current paper, the Lagrangian and Eulerian description is introduced to describe the slug flow moving along the riser.Besides, a material coordinate is added together with the position and position gradient as the state variables.The riser is discretized into two types of elements, the constant-length and variablelength elements.The variable-length element is where the slug flow locates whose velocity of the material coordinates is equal to the slug flow speed, and its movement along the riser is simulated by the moving mesh technology.Considering the fact that the enormous ratio of the length to the riser's diameter, the Euler-Bernoulli beam theory is adopted to model the riser.In this paper, the equations of motion (EOM) of the riser subjected to the slug-flow and environmental loads are derived based on the generalized D'Alembert principle.The implicit time integration method is applied to solve the derived differential-algebraic equations.First, the proposed model and the slug flow method are validated.Second, Parametric studies are performed to quantitatively identify the design conditions most affected by the slug flow.

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 score0.796
Threshold uncertainty score0.195

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 head0.034
GPT teacher head0.211
Teacher spread0.177 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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