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Record W2558602992 · doi:10.4043/27467-ms

Disconnectable Concrete Spar FPSO

2016· article· en· W2558602992 on OpenAlexaboutno aff
Anil Sablok, Andrew Blundon, Trond Landbø, Johyun Kyoung, Chad Fowlow, Svein Stromme

Bibliographic record

VenueArctic Technology Conference · 2016
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsSparIcebergMarine engineeringCatenaryHullMooringEngineeringStormGeologyStructural engineeringSea iceOceanography

Abstract

fetched live from OpenAlex

Abstract A floating platform in deep water Eastern Canada is required to withstand iceberg loads and/or be disconnected and towed away only in the event of very large approaching icebergs, leaving the mooring lines and risers in-place, support large topsides and provide large quantities of oil storage in the hull. Additionally, the platform should provide low motion response to storm and ice loads to maximize the operational uptime and facilitate the use of a large number of different riser systems including steel catenary risers (SCR). This paper presents the details of a Disconnectable Concrete Spar FPSO platform that has been configured to satisfy all the above requirements and is able to be constructed locally in Eastern Canada. The paper describes a number of key features of the Spar shaped hull, mooring and riser systems that are specifically designed to withstand large iceberg loads and other environment loads while maintaining the characteristic low motion response to storm environments. The design helps to minimize disconnection frequency due to approaching icebergs and disconnection may only be required for very large icebergs or ice islands. Additionally, the system has been designed to minimize disconnection and reconnection time.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.179
Teacher spread0.171 · 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 designBench or experimental
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

Citations4
Published2016
Admission routes1
Has abstractyes

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