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Record W1982508288 · doi:10.4043/22004-ms

Advancement of CEL Procedures to Analyze Large Deformation

2011· article· en· W1982508288 on OpenAlexaff
Kenton Pike, Shawn Kenny

Bibliographic record

VenueAll Days · 2011
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsContext (archaeology)Pipeline (software)Submarine pipelineGeotechnical engineeringPipeline transportGeologyKeelSeabedDeformation (meteorology)EngineeringMarine engineeringStructural engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Pipeline/soil interaction involves complex interplay of soil type and strength, burial depth, pipeline displacement path, contact mechanics, soil strain localization, and pipe feed-in among other parameters. Further complexity is introduced in fully coupled models to simulate ice keel/seabed/pipeline interaction events for example, where ice keel/seabed interface contact, keel bearing pressures and subgouge soil deformations are important. In order to establish confidence in more complex models, sub-interaction scenarios can be extracted and simplified. This study focuses on pipeline/soil interaction in plane strain form to examine the effects that burial depth and pipe direction of travel have on soil failure mechanisms. The coupled eulerian lagrangian (CEL) method, used in this study, is shown to provide consistent results with past work. The implications of this work in the context of modelling ice keel/seabed/pipeline interaction and model verification are discussed. Introduction Offshore and onshore arctic pipelines are often buried to provide protection from environmental loads, natural hazards and mitigate risk. These pipeline systems 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 typically involves large soil deformations and strain based failure mechanisms. Load transfer effects will develop pipe bending and axial feed-in response that may result in significant global and local pipeline deformations. In the past decade, there has been significant development in computational hardware and software technology. This has provided a robust simulation framework to address complex, nonlinear large deformation problems involving contact, material plasticity, strain localization and failure mechanisms. An example of this technology advancement is the Arbitrary Lagrangian Eulerian (ALE) formulation that has been used in the fields of fluid-structure interaction, large deformation solid mechanics and geomechanics [1]. For offshore arctic pipelines, there have been numerous studies illustrating the application of ALE techniques to analyse ice gouge events and assess load effects on buried infrastructure [2–8]. This has provided a more rational basis to address uncertainty and develop practical engineering solutions. The calibration and assessment of these numerical procedures has been primarily based on data from physical models of free-field ice gouge events at 1-g in flume tanks and at higher gravitational fields in reduced-scale centrifuge studies [9–11]. These studies, however, have only examined seabed reaction forces, soil stress and strain field distribution and horizontal subgouge soil deformations. Other factors such as geometric properties of the side and frontal berm, clearing process mechanisms, and vertical and lateral subgouge soil deformation has seen limited assessment [2,8]. Furthermore, the presence of buried infrastructure, such as a pipeline, has a significant influence on the subgouge deformation field and soil strain gradient with depth beneath the ice keel [2]. Consequently, detailed investigations are required to establish confidence in the numerical procedures with respect to data and model uncertainty, and the corresponding relative error. Demonstration of the numerical procedures to adequately simulate nonlinear contact mechanics, interface behaviour, local soil strain gradients, and failure mechanisms with minimal discretization error while maintaining computational efficiency is a demanding technical challenge. In addition, soil constitutive models may need to be improved or developed so that large soil deformation or multi-phase behavior can be simulated.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.612
Threshold uncertainty score0.278

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 head0.010
GPT teacher head0.208
Teacher spread0.199 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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