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MPS-Based Mesh-Free Particle Method for Modeling Open-Channel Flows

2011· article· en· W1974323657 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Hydraulic Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFree surfaceMechanicsOpen-channel flowInflowFinite element methodSmoothed-particle hydrodynamicsOutflowFluid dynamicsDeformation (meteorology)Eulerian pathDiscrete element methodFlow (mathematics)LagrangianPhysicsEngineeringStructural engineeringMathematicsApplied mathematicsMeteorology

Abstract

fetched live from OpenAlex

Dealing with large deformation and fragmentation of geometries and interfaces (e.g., free surfaces), the regular mesh-based Eulerian methods, such as finite-element and finite-difference methods, have difficulties in fluid-flow modeling. Recently, studies have focused on a new generation of numerical methods called mesh-free particle (Lagrangian) methods. In this study, a mesh-free particle method based on the moving-particle semi-implicit (MPS) particle-interaction model has been developed for simulation of open-channel flow. The model is able to simulate viscous fluid flow with large deformation and fragmentation of free surface in practical fields. Moreover, the model is capable of modeling open-channel problems with both inflow and outflow and inconstant numbers of particles. The model has been validated and applied to some common sample problems. The results show the reasonable accuracy of the model. The final model is capable of modeling free-surface deformation and fragmentation as well as accurate calculation of velocities in open channels.

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.

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: Methods · Consensus signal: none
Teacher disagreement score0.697
Threshold uncertainty score0.623

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 communication0.0000.001
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 head0.037
GPT teacher head0.274
Teacher spread0.237 · 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