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Record W1972744164 · doi:10.1115/omae2013-11020

Using a Dacon Scoop to Recover a Loaded Liferaft at Sea

2013· article· en· W1972744164 on OpenAlexafffundabout
Robert Brown, Kerri-Ann Evely, Graham Small, Scott N. MacKinnon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsMemorial University of Newfoundland
FundersPetroleum Research Newfoundland and LabradorSuncor Energy Incorporated
KeywordsSCOOPMarine engineeringSearch and rescueAeronauticsComputer scienceCraftInflatableEnvironmental scienceEngineeringMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

Service and supply vessels that perform standby duties in the offshore sector are equipped with a variety of resources with which to perform rescue at sea. For light to moderate sea conditions, techniques currently understood and practiced tend to involve using a fast rescue craft (FRC) to rescue survivors and subsequently transfer them to a safe haven (often a standby vessel). Rescuing evacuees in higher, more challenging sea states, however, is difficult given that it can be unsafe to launch and recover FRCs in such conditions. For these cases, many standby vessels in Eastern Canada and the North Sea are equipped with a device called a Dacon Scoop. The Dacon Scoop is a 6 to 8m semi-rigid net that is deployed directly from the side of the standby vessel and designed to rescue people directly from the water. While not a conventional use, it has been suggested that the scoop could also be used to recover small rescue craft (life rafts, lifeboats and fast rescue craft) at sea. Although life rafts provide occupants with some protection from the elements, there are still issues that can make it less than desirable to remain inside for extended periods of time if an effective means of system recovery is available. This paper presents the findings of research carried-out to determine if it is safe to use a Dacon Scoop to recover a loaded liferaft. The research trials made use of a loaded inflatable 25 person davit launched life raft and two different standby vessels 75m in length. A total of 34 tests were carried out over three days in significant wave heights up to 3.7m. Recommendations are given in the context of a human factor assessment related to the procedures, equipment and field trials experiences.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.998

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)0.0110.003

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 head0.024
GPT teacher head0.241
Teacher spread0.217 · 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; both teacher heads agree on what is shown here.

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
Published2013
Admission routes3
Has abstractyes

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