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H-Hignn: A Scalable Graph Neural Network Framework with Hierarchical Matrix Acceleration for Simulation of Large-Scale Particulate Suspensions
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Colloidal transport by active filaments
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The resistance and mobility functions of two equal spheres in low-Reynolds-number flow
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Behavior of particle swarms at low and moderate Reynolds numbers using computational fluid dynamics—Discrete element model
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Dynamics of active poroelastic filaments in Stokes flow
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Hydrodynamic interactions for single dissipative-particle-dynamics particles and their clusters and filaments
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Point-particle drag, lift, and torque closure models using machine learning: Hierarchical approach and interpretability
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Data-driven low-dimensional model of a sedimenting flexible fiber
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Rotating Membrane Inclusions Crystallize Through Hydrodynamic and Steric Interactions
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Propagation Networks for Model-Based Control Under Partial Observation
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Kokkos 3: Programming Model Extensions for the Exascale Era
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Observation of Polymer Conformation Hysteresis in Extensional Flow
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Dynamic Graph CNN for Learning on Point Clouds
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The Dynamics of Microtubule/Motor-Protein Assemblies in Biology and Physics
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Dynamics of flexible fibers in viscous flows and fluids
inferredcites →https://doi.org/10.1146/annurev-fluid-122414-034408openalex-snapshot
Simulation Methods for Particulate Flows and Concentrated Suspensions
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Interaction Networks for Learning about Objects, Relations and Physics
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Multipole Graph Neural Operator for Parametric Partial Differential Equations
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