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Advancing Offshore Operations with Digital Twin Technology: A Case Study of FLNG Operations in Offshore Environments

2024· article· en· W4402753579 on OpenAlex
Siqi Zhang, Xiaoling Liang, Ruihang Ji, Wanyue Jiang, Shuzhi Sam Ge

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTechnology Assessment and Management
Canadian institutionsUniversity of Toronto
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaNational Research Foundation
KeywordsSubmarine pipelineMarine engineeringComputer sciencePetroleum engineeringEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

This paper delineates a meticulous case study centered on the deployment of digital twin technology in Unity3D to augment operations in offshore environments, with a particular emphasis on Floating Liquefied Natural Gas operations. It encompasses the integration of real-time meteorological data, the application of a Proportional-Integral-Derivative controller for refined vessel maneuvering, and the incorporation of an advanced voice navigation interface. The primary objective of this research is to substantially elevate the controllability, predictability, and operational efficacy within the realm of offshore asset management. The findings of this study significantly contribute to the enhancement of strategic decision-making frameworks and propel forward-looking innovations in the offshore sector, culminating in heightened operational efficiency and fortified risk management strategies.

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.

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: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.005
GPT teacher head0.233
Teacher spread0.228 · 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

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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