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Record W1580348360

Finite-element modelling of acoustic wave scattering from fluid, rigid and elastic objects

2005· article· en· W1580348360 on OpenAlexaffvenue
Omar Falou, J. Carl Kumaradas, Michael C. Kolios

Bibliographic record

VenueCanadian acoustics · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFinite element methodScatteringAcousticsFluid–structure interactionComputationSPHERESAcoustic wavePhysical acousticsWave propagationStructural acousticsPhysicsMechanicsVibrationComputer scienceOptics
DOInot available

Abstract

fetched live from OpenAlex

A finite element model (FEM) of acoustic wave propagation through 3-D arbitrary-shaped structures is developed to solve the problem of high frequency acoustic scattering. The FEMLAB&reg software package was used to develop and solve acoustic scattering models from fluid, rigid, and elastic spheres immersed in a fluid medium, for which analytical solutions are available. The entire computation domain is modeled as a sphere filled with fluid domains. It is found that the FEM provided accurate predictions of wave scattering by three types of scatterers, fluid, rigid immovable, and elastic.

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 categoriesInsufficient payload (model declined to judge)
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 score0.503
Threshold uncertainty score0.999

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)0.0020.000

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 head0.036
GPT teacher head0.217
Teacher spread0.181 · 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

Citations6
Published2005
Admission routes2
Has abstractyes

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