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Record W2183762361 · doi:10.1115/omae2015-41292

CIP and Parallel Computing Based Numerical Solutions of 3-D Slamming Problems

2015· article· en· W2183762361 on OpenAlexaff
Peng Wen, Wei Qiu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSlammingDomain decomposition methodsConjugate gradient methodBiconjugate gradient stabilized methodComputationComputer scienceInterpolation (computer graphics)Computational scienceAdvectionApplied mathematicsCartesian coordinate systemComputational fluid dynamicsMessage Passing InterfaceAlgorithmMathematical optimizationMathematicsParallel computingMechanicsGeometryMessage passingFinite element methodPhysicsEngineering

Abstract

fetched live from OpenAlex

This paper presents the further development of numerical simulation method to solve 3-D highly non-linear slamming problems using parallel computing algorithms. The water entry problems are treated as multi-phase problems (solid, water and air) and governed by the Navier-Stokes (N-S) equations. They are solved by the three-dimensional constrained interpolation profile (CIP) method. The interfaces between different phases are captured using density functions. In the computation, the 3-D CIP method is employed for the advection phase of the N-S equations and a pressure-based algorithm is applied for the non-advection phase. The bi-conjugate gradient stabilized method (BiCGSTAB) is utilized to solve the linear equation systems. A Message Passing Interface (MPI) parallel computing scheme was implemented in the computations. For the parallel computations, the three-dimensional Cartesian decomposition of the computational domain was used. The speed-up performance of various decomposition schemes were studied. Validation studies were carried out for the water entry of a 3-D wedge and a 3-D ship section with prescribed velocities. The computed slamming force, pressure distribution and free-surface elevations are compared with experimental results and numerical results by other methods.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.217

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 head0.030
GPT teacher head0.237
Teacher spread0.207 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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