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Record W2134477988 · doi:10.22059/jac.2013.7802

Numerical Modeling of Launching Offshore Jackets from Transportation Barge & the Significance of Water Entry Forces on Horizontal Jacket Members

2013· article· en· W2134477988 on OpenAlexaff
Nikzad Nourpanah, Moharram Dolatshahi Pirooz

Bibliographic record

VenueInternational Symposium on Algorithms and Computation · 2013
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBARGESubmarine pipelineMarine engineeringTrajectoryEngineeringImpactStructural engineeringFictitious forceGeotechnical engineeringGeologyMechanicsPhysics

Abstract

fetched live from OpenAlex

Development of a numerical model which describes launching of offshore jackets from barge is presented in this paper. In this model, in addition to capabilities of commercial softwares, water entry forces on jacket members and an implicit Newmark solution technique are included. The results are in general agreement with other numerical software’s available (SACS). Fluid forces acting on jacket and the importance of each one is discussed. It is observed that water entry forces on horizontal jacket members are very significant and may locally govern the design of these members. This force is more important for horizontal slender members near the mud-line, which do not experience significant environmental loading in operating conditions. Therefore the water entry impact force with large magnitude can cause over-stress and/or ovalling of near mud-line members. It is also observed that taking water entry forces in account modifies the jacket trajectory only in a little extent.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.008
GPT teacher head0.224
Teacher spread0.216 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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