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Record W2025247953 · doi:10.1115/pvp2005-71685

Numerical Study of Liquid Dynamics in Partially Filled Circular Tanks

2005· article· en· W2025247953 on OpenAlexaff
Liang Xu, Liming Dai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsSlosh dynamicsDiscretizationMechanicsDynamics (music)Boundary value problemTransient (computer programming)Eigenvalues and eigenvectorsStorage tankSquare (algebra)Equations of motionFlow (mathematics)Classical mechanicsPhysicsGeometryMathematicsMathematical analysisComputer scienceAcousticsThermodynamics

Abstract

fetched live from OpenAlex

The liquid dynamics in partially filled circular tanks has been studied by numerically solving the natural frequencies and transient liquid motion. The governing equations for liquid in tanks are based on the potential flow theory. Instead of direct discretization in the 2D circular area, the governing equations are rearranged in such a way that the discretization is performed in a fixed square area by continuous coordinate mappings to overcome the difficulties in dealing with the boundary conditions on the circular edge and the free surface. The natural frequencies of liquid sloshing in partially filled circular tanks are determined by solving generalized eigenvalue problem of liquid under different fill levels. Transient liquid motion is simulated when the tank is subjected to motion in the lateral direction, which is represented by different prescribed lateral accelerations. The forces caused by the change of liquid pressure on the tank walls are calculated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.008
GPT teacher head0.239
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2005
Admission routes1
Has abstractyes

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