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Record W2220682523 · doi:10.1115/omae2015-42157

Hydrodynamic Performance of a FPSO in Highly Oblique Flow Conditions

2015· article· en· W2220682523 on OpenAlexfundno aff
Mohammed Islam, Fatima Jahra, Ron Ryan, David Molyneux, Lee Hedd

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicShip Hydrodynamics and Maneuverability
Canadian institutionsnot available
FundersAtlantic Canada Opportunities Agency
KeywordsFroude numberHullInflowMechanicsOblique caseFlow (mathematics)Moment (physics)Reynolds-averaged Navier–Stokes equationsMarine engineeringJet (fluid)TrimGeologyComputational fluid dynamicsPhysicsStructural engineeringEngineeringClassical mechanics

Abstract

fetched live from OpenAlex

The capability of the viscous-flow solver Star-CCM+ to simulate the flow around a ship in steady oblique motion has been studied. To obtain insight into the reliability and accuracy of the results, grid dependency studies were conducted. Local flow quantities as well as integral variables were compared to measurement values. A FPSO hull form was considered for the simulations as well as experimental assessment of the resistance and flow field at multiple oblique flow conditions. The measurements and simulations have been completed at one draft, one Froude numbers and in 7 inflow conditions (0° to 180° with 30° increments). The measurements and predictions were made for the resistance in the inflow direction, side force and yawing moment. Additionally, the pressure and velocity distributions around the hull at multiple cross-sections are presented derived from the RANS predictions. Qualitatively, promising results are obtained. For practical purposes however, the accuracy of the results may require further improvement. For the current calculations, the predicted yaw moment is close to the measurements but the side force is under-predicted. Reasons for these discrepancies might be the neglect of trim and sinkage for the FPSO and of the insufficient grid resolution at the bow and stern. This should be studied in future research.

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: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.351

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 head0.009
GPT teacher head0.209
Teacher spread0.199 · 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".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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