MétaCan
Menu
Back to cohort
Record W4400182241 · doi:10.1016/j.cma.2024.117172

A 3D phase-field based Eulerian variational framework for multiphase fluid–structure interaction with contact dynamics

2024· article· en· W4400182241 on OpenAlexaff
Xiaoyu Mao, Biswajeet Rath, Rajeev K. Jaiman

Bibliographic record

VenueComputer Methods in Applied Mechanics and Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFluid–structure interactionEulerian pathMechanicsPhase (matter)Dynamics (music)Multiphase flowField (mathematics)Classical mechanicsComputational fluid dynamicsPhysicsStatistical physicsComputer scienceMathematicsApplied mathematicsFinite element methodThermodynamicsLagrangian

Abstract

fetched live from OpenAlex

Using a fixed Eulerian mesh, interface-capturing approaches such as volume-of-fluid, level-set and phase-field methods have been successfully utilized for a broad range of moving boundary problems involving multiphase fluids and single-phase fluid–structure interaction. Nevertheless, multiphase fluids interacting with multiple solids are rarely explored, especially for large-scale finite element simulations with contact dynamics. In this work, we introduce a novel parallelized three-dimensional fully Eulerian variational framework for simulating multiphase fluids interacting with multiple deformable solids subjected to solid-to-solid contact. In the framework, each solid or fluid phase is identified by a standalone phase indicator. Moreover the phase indicators are initialized by the grid cell method, which restricts the calculation to several grid cells instead of the entire domain and provides efficiency for modeling evolving interfaces on a fixed mesh. A diffuse interface description is employed for a smooth interpolation of physical properties across the phases, yielding unified mass and momentum conservation equations for the coupled dynamical interactions. For each solid object, temporal integration is carried out to track the strain evolution in an Eulerian frame of reference. The coupled differential equations are solved in a partitioned manner and integrated via nonlinear iterations. We first verify the framework against reference numerical data in a two-dimensional case of a rotational disk in a lid-driven cavity flow. The case is generalized to a rotational sphere in a lid-driven cavity flow to showcase large deformation and rotational motion of solids and examine the convergence in three dimensions. We then simulate the falling of an immersed solid sphere on an elastic block under gravitational force to demonstrate the translational motion and the solid-to-solid contact in a fluid environment. Finally, we demonstrate the capability of our proposed framework for a ship–ice interaction problem involving multiphase fluids with an air–water interface and contact between a floating ship and ice floes. • Unified continuum description of fluid–solid interaction via phase-field theory. • Multiphase fluid flow with multiple solids subjected to solid–solid contact. • 3D parallelized implementation for phase-field finite element simulation. • Novel diffuse interface initialization of interface with complex geometry. • Demonstration for ship–ice interaction with free-surface and contact dynamics.

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)0.001
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.339
Teacher spread0.321 · 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

Citations13
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueComputer Methods in Applied Mechanics and EngineeringSame topicAdvanced Numerical Methods in Computational MathematicsFrench-language works237,207