General & Applied Physics · Physics & Astronomy
Fluid Dynamics
The newest papers in Fluid Dynamics that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
101 papers, from 7 September 2026 to 5 November 2026: 101 arXiv preprints.
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The typical red cell makes too little vacuole material for coalescence to build the large vacuoles of pocked cells
Red blood cells carrying intracellular vacuoles, called pocked cells, are a sensitive marker of splenic function: about 0.5% of cells in healthy people, 20 to 70% after splenectomy.Extreme-Scale Super-Resolution of Homogeneous Turbulence from a Single Realization
Homogeneous turbulent flows exhibit recurring multiscale structures across spatially separated regions, suggesting that a single flow realization may contain sufficient information to learn…High-fidelity Three-Dimensional Flow Field Reconstruction Driven by Turbulent Fluid Dynamics
High-fidelity three-dimensional turbulent flow fields are essential for scientific and engineering analyses, yet obtaining them through direct numerical simulation or high-resolution measurements…Probabilistic Simulation of Gas-Liquid Interfaces with Coupled Flow Matching on Spherical Harmonics
Bubbly flows involve strongly coupled bubble motion, deformation, and hydrodynamic interactions, making high-fidelity simulation computationally expensive.Physics Foundation Models for Efficient Control of Fluid Flows
We investigate whether a physics foundation model (PFM) pretrained for PDE forecasting can be repurposed for closed-loop fluid-flow control.Cova-PINN: Cross-Domain Conservation Physics-Informed Neural Network for Fluid-Solid Conjugate Heat Transfer in Complex Geometries
Multi-domain physics-informed neural networks (PINNs) flexibly model medium-specific representations to solve fluid--solid conjugate heat transfer (CHT).Analytical Modeling of Open- and Closed-Loop Dispersive Molecular Communication Channels with Pulsatile Flow
Molecular communication (MC) is a communication paradigm in which information is conveyed through the release, propagation, and reception of molecules.PoreML: A Data-Driven Framework for Learning Multiphase Flow in Porous Media
Multiphase flow in porous microstructures is central to CO$_2$ storage, fuel-cell operation, and flip-chip packaging.Conditional Flow Matching for Generation of 3D Multi-variable Instantaneous Urban Microclimate Fields
Rapid and accurate prediction of urban wind and temperature fields is important for urban microclimate design and climate adaptation.Gen-PINNs: Generative Adversarial Physics Informed Neural Networks for solving partial differential equations
Physics-Informed Neural Networks (PINNs) are a widely used data-free method for solving Partial Differential Equations (PDEs) using machine learning.Reflex instabilities I: Boundaries makes grid-based disc simulations frame-dependent
If the mass distribution within an accretion disc is asymmetric, it will exert a gravitational pull on its central object.Reflex instabilities II: The reflex motion of the central object drives at least seven instabilities in accretion discs
This series of papers studies the stability of accretion discs to the reflex motion of the central object under the gravitational pull of the disc itself.Accelerated search for global extrema in structured quantum signals
Extreme values of a physical system are rare by definition, yet they can govern some of its most consequential and anomalous behavior.Physics-Informed Method of Group Data Handling: Adaptive Construction of Functional Representations with an Application to the Navier-Stokes Equations
Physics-informed computational methods usually optimize parameters within a functional representation whose structure is fixed in advance.Do Better Scores Mean Better Physics? Physics-Grounded Explanations for Sim2Real Neural Operators
Machine-learning surrogates accelerate physical simulation, but lower prediction error need not coincide with lower error in physically relevant flow statistics.Probabilistic Symbolic-Distillation Model of Droplet Collision for Spray Simulation at High Ambient Pressures
Droplet collision governs droplet population dynamics in many chemical engineering processes, such as spray drying, spray cooling, agricultural spraying, and combustion.A shape-similarity latent space for fluid interfaces: invertible reduced-order modelling of droplet morphology
A droplet breaks up in tens of microseconds, and a recording captures perhaps a dozen frames.Physics-Informed Neural Networks for Depth-Averaged Avalanche Dynamics
Accurate prediction of avalanche motion is essential for hazard assessment in mountainous terrain.Learning in the Transverse Subspace: A Minimal Representation for Divergence-Free Operator Learning
Divergence-free vector fields are fundamental state variables in incompressible flows and many PDE systems.Staying on the Attractor: Supervising Neural Surrogates of 3D Turbulence Where They Leave It
Neural surrogates are trained to predict 3D turbulent flows in place of direct numerical simulation (DNS).
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