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Record W2069181045 · doi:10.1115/omae2004-51006

Non Linear Seismic Pile Soil Structure Interaction Analysis of Piles in Offshore Platforms

2004· article· en· W2069181045 on OpenAlexaff
Mehrdad Kimiaei, Mohsen Ali Shayanfar, M. Hesham El Naggar, Ali Akbar Aghakouchak

Bibliographic record

Venue23rd International Conference on Offshore Mechanics and Arctic Engineering, Volume 1, Parts A and B · 2004
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsWestern University
FundersUniversity of California, Davis
KeywordsPileDissipationNonlinear systemStructural engineeringFoundation (evidence)Finite element methodGeotechnical engineeringRadiation dampingSoil structure interactionStiffnessSubmarine pipelineDiscontinuity (linguistics)GeologySeismic analysisBeam (structure)Seismic loadingEngineeringPhysics

Abstract

fetched live from OpenAlex

Pile supported offshore platforms in seismically active areas should be designed to survive severe earthquake excitations with no global structural failure. It is often required to perform nonlinear seismic analysis of offshore platforms that accounts for soil nonlinearity, discontinuity condition at pile soil interfaces, energy dissipation through soil radiation damping and structural nonlinear behaviours of the piles. In this study a BNWF (Beam on Nonlinear Winkler Foundation) model is incorporated into a finite element program (ANSYS) and it is used to compute the lateral response of piles subjected to seismic loading. The soil stiffness is established using the P-Y curve. The results of equivalent linear earthquake free field ground motion analyses are used as the input excitations at support nodes of the model. The components and advantages of this practical ANSYS model in seismic pile soil structure interaction analyses are discussed and addressed in detail. Computed responses compared well with the experimental test results. Sensitivity of the results to model parameters and site response calculations are evaluated.

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 categoriesMeta-epidemiology (narrow)
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 score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.012
GPT teacher head0.223
Teacher spread0.211 · 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.

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

Citations5
Published2004
Admission routes1
Has abstractyes

Explore more

Same venue23rd International Conference on Offshore Mechanics and Arctic Engineering, Volume 1, Parts A and BSame topicGeotechnical Engineering and Soil MechanicsFrench-language works237,207