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Record W4320916622 · doi:10.1201/9781003399759-12

Numerical simulation of ship motion and non-linear sea loads of a modern frigate in regular waves

2023· book-chapter· en· W4320916622 on OpenAlexaboutno aff
Ziwen Zhang, Nan Ma, Qiqi Shi

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicShip Hydrodynamics and Maneuverability
Canadian institutionsnot available
Fundersnot available
KeywordsMotion (physics)Marine engineeringShip motionsGeologyResponse amplitude operatorGeodesyEngineeringClassical mechanicsPhysicsHull

Abstract

fetched live from OpenAlex

Ship design, especially design of warships, requires precise predictions of sea loads in extreme wave conditions. In recent years, with the enlargement tendency of ships, the stiffness of ship hull has become weaker, resulting in more significant non-linear springing and whipping loads, which should be paid more attention to. This paper presents a numerical study of non-linear sea loads of a modern Canadian frigate in regular head seas based on a time-domain non-linear hydro-elastic prediction program. Non-linear Froude-Krylov forces, slamming forces and restoring forces are taken into consideration. Transfer matrix method is used to solve natural vibration of dry mode as an input of the hydro-elastic program. The numerical results are provided for comparison with model tests conducted by McTaggart et al. This numerical study will also be a part of the benchmark study of MARSTRUCT, which will provide a reference for an appropriate uncertainty analysis procedure in the future.

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 score0.389
Threshold uncertainty score0.727

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 head0.018
GPT teacher head0.232
Teacher spread0.213 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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