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Record W1568366356

Numerical Analysis of the Behavior of Suction Caissons in Clay

2003· article· en· W1568366356 on OpenAlexaff
Jianchun Cao, Ryan Phillips, Radu Popescu, J.M.E. Audibert, Z. Al-Khafaji

Bibliographic record

VenueInternational Journal of Offshore and Polar Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsMemorial University of NewfoundlandCentre For Cold Ocean Resources Engineering
Fundersnot available
KeywordsCentrifugeSuctionFinite element methodCaissonDisplacement (psychology)Geotechnical engineeringMechanicsStructural engineeringMaterials scienceEngineeringMechanical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

This paper presents the development of a finite element model for simulating the behavior of suction caissons subjected to vertical loading, and the validation of the numerical model based on centrifuge experimental results. The pull out load versus displacement (Pu-d) curve obtained from finite element analyses (FEA), using the passive suction recorded in the centrifuge tests, was in close agreement with that obtained using the centrifuge pull out tests. Numerical simulation of passive suction is still a challenging problem, which is not fully solved at the present time. A new method, in which the water inside the caisson is simulated by a very soft poro-elastic material, was used to simulate the development of passive suction. Although the passive suction versus pull out displacement curve obtained using the FEA was slightly different from that obtained from the centrifuge tests, the magnitude of the maximum suction was almost the same, and the pull out force with displacement curve obtained using the FEA was in close agreement with that obtained from the centrifuge tests.

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: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.255

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 head0.006
GPT teacher head0.222
Teacher spread0.216 · 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

Citations28
Published2003
Admission routes1
Has abstractyes

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