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Record W3115116033 · doi:10.1115/omae2020-19290

The Status of Arctic Offshore Pipeline Standards and Technology

2020· article· en· W3115116033 on OpenAlexaffabout
Mike Paulin, Jonathan Caines, Amy Davis, Duane DeGeer, Todd Cowin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsIntecsea (Canada)
Fundersnot available
KeywordsSubmarine pipelineArcticPipeline transportPipeline (software)SubseaEngineeringEnforcementEnvironmental planningEnvironmental resource managementMarine engineeringRisk analysis (engineering)Environmental scienceCivil engineeringBusinessOceanographyGeologyEnvironmental engineeringPolitical scienceMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Offshore pipelines in an Arctic or ice-covered environment face unique challenges different from traditional subsea pipeline design. In 2018, Intecsea as lead consultancy delivered a report to the US Bureau of Safety and Environmental Enforcement (BSEE) Alaska Region which provided a comprehensive review and gap analysis of the Status of Arctic Pipeline Standards and Technology. The objective of this study was to provide BSEE with a comprehensive review and gap analysis of current offshore Arctic pipeline design standards, codes and regulations pertaining to design and development of offshore pipelines in the Arctic, and to report on the state-of-the-art and emerging technologies for offshore pipelines in Arctic applications. Project development information from nine existing offshore Arctic pipelines in the U.S., Canada, and Russia was summarized, as well as guidelines and industry best-practice for monitoring and leak detection. This paper provides an overview of the results of this study; what offshore Arctic-specific pipeline design and construction challenges may entail, how they have been overcome in past projects, perceived gaps in regulations, and technology advancements that may help with future developments. This paper also summarizes the results of a comprehensive review and gap analysis of Arctic pipeline standards, assessment of the suitability of a single-walled versus pipe-in-pipe system for Arctic applications and presents information on some of the advancements in pipeline design, installation, operations and repair solutions that may be applicable to an Arctic environment.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.237

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 head0.007
GPT teacher head0.204
Teacher spread0.198 · 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 designOther design
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
Published2020
Admission routes2
Has abstractyes

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