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Record W2053991156 · doi:10.4043/21998-ms

Continuum Modelling Framework for Local Buckling Response of Plain and Girth Welded Pipes

2011· article· en· W2053991156 on OpenAlexaff
Ali Fatemi, Shawn Kenny

Bibliographic record

VenueOffshore Technology Conference · 2011
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBucklingStructural engineeringBending momentFinite element methodPipeline transportBoundary value problemGeotechnical engineeringEngineeringGeologyMathematicsMechanical engineering

Abstract

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Abstract In this paper, the significance of boundary conditions (L/D ratio), initial geometric imperfections, anisotropic material properties, and material constitutive model on the local buckling response of plain and girth welded pipes was evaluated using continuum finite element modelling procedures. A numerical model was developed, using the finite-element simulator ABAQUS/Standard, to predict the local buckling and post-buckling response of high strength pipelines subject to combined state of loading. The numerical procedures were calibrated using test data from large-scale experiments examining the local buckling of high strength linepipe. The moment and strain response estimates, predicted by the numerical simulation tool, was consistent with the experimental data well into the post-yield range. As the models with high L/D ratio exhibit global Euler-type response, a numerical algorithm was developed to calculate the local section moment response based on FE predictions. Introduction Arctic pipelines may be subject to large deformation geohazards such as ice gouging, frost heave, thaw settlement, seismic fault movement and lateral spreading due to liquefaction. The imposed ground displacement field and load transfer effects will develop a pipe bending and axial feed-in response that may result in local pipeline buckling response. For these design conditions, mechanical performance criteria are generally based on strain limits in order to develop practical and cost-effective engineering solutions. Although there have been a significant number of investigations on the bending and local buckling response of pipelines over the past 80 years, which include analytical, physical and computational modelling studies, there remains some areas of uncertainty [1–11]. Some of these areas include parameter characterization and quantification on effects of capacity reduction associated with initial geometric imperfections of the pipe body, residual stress and geometric imperfections associated with girth welding processes, material anisotropic behavior and discontinuous yielding [6,12,13]. This paper will address these issues through discussion of studies conducted by the authors, using continuum finite element modelling procedures, and reference to other publications. Numerical Modelling Procedures The numerical modeling procedures were developed using the commercial software package ABAQUS/Standard. These numerical modeling procedures were calibrated with full scale tests conducted on linepipe segments with a 3.5 L/D ratio. Zimmerman et al. [14] presented a generalized description of the experimental apparatus and test procedure. The FE modelling procedures simulated experimental tests on a linepipe segment subject to end rotation, internal pressure and axial force. A typical FE model is illustrated in Figure 1. The pipeline was modeled using a reduced integrated shell element (S4R). The mesh topology was an element length of 20 mm on the pipeline length and circumference, which was based on a mesh convergence study [15]. The mesh density was selected to maintain a consistent topology across the range the two segment lengths examined. In the experimental test program, for pipeline segment lengths of 3.5 D, end support collars were used to mitigate the effects of boundary conditions on the local buckling response. In this study, the support collars were assumed to have perfect contact with the pipeline segment. The support collars were modeled with a nominal wall thickness equal to the nominal pipeline wall thickness and a length of 0.5D.

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: none
Teacher disagreement score0.005
Threshold uncertainty score0.009

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.028
GPT teacher head0.233
Teacher spread0.205 · 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

Citations4
Published2011
Admission routes1
Has abstractyes

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