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Record W3113810463 · doi:10.1115/omae2020-18525

Validation of Predictions of Wire Stress of Flexible Pipe With Damaged Tensile Armor Wires Under Combined Tension and Bending

2020· article· en· W3113810463 on OpenAlexaff
Krassimir Doynov, Gabriel Rombado, Nathan Cooke, Arya Majed

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsIntecsea (Canada)
Fundersnot available
KeywordsStructural engineeringFinite element methodBendingTension (geology)Nonlinear systemMaterials scienceArmourAxial symmetryStress (linguistics)Ultimate tensile strengthTensile testingDynamic TensionComposite materialMechanicsEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The nonlinear kinematic response of a damaged 2.5” flexible pipe under combined tensile and bending cyclic loads is simulated and compared to experimental results. High fidelity finite element model substructures are constructed for intact and broken outer and inner armor wire configurations and assembled in a nonlinear dynamic substructuring (NDS) framework to efficiently simulate the full-scale test configurations. Overall, 12 analysis configurations involving all intact wires, up to 4 broken outer wires, and 2 and 4 broken inner wires combined with 4 broken outer wires are constructed. Each analysis configuration is first preloaded axially and then subject to multiple cycles of (i) pure tension and (ii) combined tension and bending. For each case, tensile armor wire strains are extracted from the simulations and compared to strain measurements from the test. For all cases, numerical predictions and test measurements agree well accurately capturing the redistribution of strains into the adjacent intact wires which result in stress concentration factors. This comprehensive demonstration of accurate capture of flexible pipe damaged wire kinematics by high fidelity finite element models and nonlinear simulations has direct applications to flexible pipe integrity management and remnant life assessments. Given that the NDS framework allows highly efficient computation, it is now feasible to execute real-time irregular wave local fatigue simulations with finite element models that include damaged wire data from physical inspections to more accurately predict remnant life.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.229

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 head0.021
GPT teacher head0.212
Teacher spread0.191 · 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 designBench or experimental
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

Citations1
Published2020
Admission routes1
Has abstractyes

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