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Record W3100601856 · doi:10.1115/detc2001/cie-21274

Response of Submerged Structures by the Finite Element-Cum-Boundary Element Method

2001· article· en· W3100601856 on OpenAlexaff
C.W.S. To, M. O'Grady

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsFinite element methodMixed finite element methodSingularityConvergence (economics)Extended finite element methodBoundary knot methodShell (structure)Computer scienceSmoothed finite element methodBoundary element methodBoundary (topology)Fluid–structure interactionEigenvalues and eigenvectorsApplied mathematicsMathematicsMathematical analysisStructural engineeringMechanical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract A double asymptotic approximation based finite element-cum-boundary element approach for fluid-structure interaction problems is being proposed. In particular a staggered solution scheme has been applied to the analysis of various coupled fluid-structure systems. A stabilization scheme by reformulation, proposed by DeRuntz et al. was employed to circumvent the instability problem. In addition, the singularity in the excitation term was eliminated through a variable transformation as suggested by Everstine. Another feature of the present work is its incorporation of the hybrid strain based lower order triangular shell finite element developed by To and Liu. The eigenvalue solution exhibits high convergence rate for the particular shell finite element employed. The responses calculated exhibit the effectiveness of the proposed approach with application of the aforementioned shell finite element in dealing with three dimensional fluid-structure interaction problems. The reduction in problem size that this approach affords allows these complex interaction problems to be dealt with in a desktop engineering workstation environment, as opposed to the mainframe and supercomputer arenas where they have been implemented in the past.

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)0.001
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.304
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.025
GPT teacher head0.336
Teacher spread0.311 · 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
GenreMethods

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
Published2001
Admission routes1
Has abstractyes

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