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Record W2027519996 · doi:10.1115/1.4023795

Preliminary Assessment of the Importance of Platform–Tendon Coupling in a Tension Leg Platform

2013· article· en· W2027519996 on OpenAlexaff
Marco Masciola, Meyer Nahon, Frederick Driscoll

Bibliographic record

VenueJournal of Offshore Mechanics and Arctic Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsTendonCoupling (piping)Tension (geology)Sensitivity (control systems)GeneralitySpring (device)Structural engineeringDynamics (music)Set (abstract data type)DragComputer scienceSimulationControl theory (sociology)EngineeringMechanicsMechanical engineeringAcousticsPhysicsElectronic engineeringClassical mechanicsAnatomy

Abstract

fetched live from OpenAlex

This paper presents performance metrics that can be used to evaluate the response sensitivity of a tension leg platform (TLP) to its tendons. An uncoupled TLP model ignores the intrinsic dynamics and environmental loads on the cables by treating each tendon as an ideal massless spring. A coupled TLP system, in contrast, considers the effects of distributed mass and drag along the tendon. Under certain operating conditions, an uncoupled dynamics model can produce results comparable to its coupled counterpart. This paper defines the conditions under which it is acceptable to model a TLP tendon as a linear spring, as opposed to one that considers the cable dynamics. The analysis is performed in the frequency domain and, for generality, the results are nondimensionalized. The findings indicate that a more elaborate set of conditions than the platform–to–cable mass ratio must be satisfied for the two models to provide similar results. To conclude this study, two simulations are performed and compared against the performance metrics derived in this paper.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.318

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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 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

Citations6
Published2013
Admission routes1
Has abstractyes

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