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Record W4408645480 · doi:10.1016/j.apor.2025.104526

Fatigue damage assessment of steel catenary risers in the touchdown zone accounting for soil remoulding and reconsolidation effects

2025· article· en· W4408645480 on OpenAlexafffund
Hossein Janbazi, Hodjat Shiri

Bibliographic record

VenueApplied Ocean Research · 2025
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsCatenaryTouchdownGeotechnical engineeringGeologyEnvironmental scienceEngineeringStructural engineeringGeography

Abstract

fetched live from OpenAlex

The design of steel catenary risers (SCRs) is mainly affected by fatigue performance in the touchdown zone (TDZ), where the riser cyclically interacts with the seabed. This cyclic motion leads to seabed soil softening and remoulding. However, over an extended period of riser operations, the seabed soil undergoes a drainage because of small motion amplitudes of the floating vessel during calm weather or a limited contact with the seabed due to vessel relocation. This may cause recovery of the soil strength associated with excess pore pressure dissipation resulting in an extra fatigue damage accumulation in the TDZ. In the current study, a global SCR analysis has been conducted using a series of coded springs along the TDZ to model advanced SCR-seabed interactions. The instantaneous undrained shear strength of the soil is determined by using a recently developed effective stress framework. The effects of soil remolding and consolidation were integrated during both the dynamic motion of the SCR and intervening pause periods within the critical-state soil mechanics. The model updates the SCR-soil interaction spring at every time increment of dynamic analysis, calculating the cross-section stress range while taking into account the overall configuration of the riser on the seabed. The study showed that the consolidation may result in an increased fatigue damage of about 23 %, which is currently neglected by the existing non-linear SCR-soil interaction models.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.359
Teacher spread0.316 · 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 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

Citations2
Published2025
Admission routes2
Has abstractyes

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