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Record W3128347158 · doi:10.1115/1.4049122

A Theoretical Model for Ship–Wave Impact Generated Sea Spray

2020· article· en· W3128347158 on OpenAlexafffund
Shafiul Mintu, David Molyneux, Bruce Colbourne

Bibliographic record

VenueJournal of Offshore Mechanics and Arctic Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsMemorial University of Newfoundland
FundersMitacs
KeywordsSea sprayFlux (metallurgy)DeckSpray characteristicsMarine engineeringEnvironmental scienceHullSpray nozzleFull scaleMeteorologyMechanicsEngineeringMaterials scienceStructural engineeringPhysicsNozzleMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Spray generated by ships traveling in cold oceans often leads to topside icing, which can be dangerous to vessels. Estimation of the spray flux is a first step in predicting icing accumulation. The amount of spray water, the duration of exposure to the spray, and the frequency at which the spray is generated are all important parameters in estimating the spray flux. Most existing spray flux formulae are based on field observations from small fishing vessels. They consider meteorological and oceanographic parameters but neglect the vessel behavior. Ship heave and pitch motions, together with ship speed, determine the frequency of spray events. Thus, the existing formulae are not generally applicable to different sizes and types of vessels. This paper develops simple methods to quantify spray properties in terms that can be applied to vessels of any size or type. Formulae to estimate water content and spray duration are derived based on principles of energy conservation and dimensional analysis. To estimate spray frequency considering ship motions, a theoretical model is proposed. The model inputs are restricted to ship’s principal particulars, operating conditions, and environmental conditions. Wave-induced motions are estimated using semi-empirical analytical expressions. A novel spray threshold is developed to separate deck wetness frequency from spray frequency. Spray flux estimates are validated against full-scale field measurements available in the open literature with reasonable agreement.

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 score0.834
Threshold uncertainty score0.615

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 head0.022
GPT teacher head0.224
Teacher spread0.203 · 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

Citations14
Published2020
Admission routes2
Has abstractyes

Explore more

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