MétaCan
Menu
Back to cohort
Record W2032560443 · doi:10.4043/25932-ms

Ultra-Deepwater Steel Riser Systems Hosted on FPSOs Offshore Brazil

2015· article· en· W2032560443 on OpenAlexaff
Manuel Moreu, Miguel Taboada, Alberto Taboada, Cortes Garcia, Jaime Moreu, Alaa Mansour

Bibliographic record

VenueOffshore Technology Conference · 2015
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsIntecsea (Canada)
Fundersnot available
KeywordsHullDisplacement (psychology)Submarine pipelineMarine engineeringStructural engineeringStress (linguistics)Point (geometry)EngineeringGeologyGeotechnical engineeringMathematics

Abstract

fetched live from OpenAlex

Abstract This paper investigates the potential feasibility of SCRs hosted on FPSOs in offshore Brazilian ultra-deepwater regarding to fatigue life at the Touch-Down Zone (TDZ) when the riser system is hanged off from a centered moonpool instead of from the unit's side. A case study is presented here in order to provide a suitable starting point for the study a 2 MMbbl FPSO has been preliminary dimensioned and the focus has been set on wave induced motions fatigue loading. Wave induced motions at two porch locations, one connected to the hull outer shell and another connected at the moonpool of the FPSO, are calculated and used as forced-displacement boundary conditions in a detailed riser FEM analysis whose stress cycle time series are eventually calculated to provide an estimation of the fatigue damage at the TDZ between the two locations. Despite the conservatism that this approach might introduce regarding the estimation of the fatigue life of the SCR due to the fact that the damage is concentrated in quite a few elements, the results from the calculations show a significant decrease in the wave fatigue damage at the TDZ when the risers are installed inside the moonpool.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.227
Teacher spread0.205 · 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 designNot applicable
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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueOffshore Technology ConferenceSame topicOffshore Engineering and TechnologiesFrench-language works237,207