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Record W2164792956 · doi:10.5267/j.esm.2013.09.004

Numerical analysis of hydrodynamic interaction between the linear waves of Caspian Sea and Amirkabir semi-submersible drilling platform

2013· article· en· W2164792956 on OpenAlexvenueno aff
Rahmatollah Ghajar, Seyed Mohammad Navid Ghoreishi

Bibliographic record

VenueEngineering Solid Mechanics · 2013
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsMarine engineeringDrillingGeologyFluid–structure interactionMechanicsEngineeringPhysicsFinite element methodMechanical engineeringStructural engineering

Abstract

fetched live from OpenAlex

Semi-submersible drilling platforms are huge bulk structures for extracting the oil products from great depth of seas. For such bulk structures, the Morrison's equations are no longer valid for determining the loads applied to the semi-submersible drilling platforms. The diffraction theory should be used for evaluating the hydrodynamic interactions between the platform and the sea waves. In this theory, the Laplace equation is solved by considering the boundary conditions of the diffraction theory. In this paper, after a brief description of the diffraction theory, the hydrodynamic interactions between the Iran's Amirkabir semi-submersible drilling platform and the regular linear waves of Caspian Sea is investigated numerically using boundary element method in the ANSYS/AQWA software. The induced waves exciting forces and moments with different wave heading angles are estimated for six degrees of freedom relative to the waves frequencies using the diffraction theory. The performed hydrodynamic analysis is also validated with the previous works performed for Spar platforms. }}

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 score0.322
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.226
Teacher spread0.218 · 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

Citations10
Published2013
Admission routes1
Has abstractyes

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