1229 papers
Fluid dynamics explores how liquids and gases move, shaping everything from weather patterns to the flow of blood through our veins. This field bridges the gap between abstract mathematical equations and the tangible forces that drive our physical world, offering insights into turbulence, aerodynamics, and fluid behavior in complex environments.
On Gist.Science, we process every new preprint in this category directly from arXiv to make cutting-edge research accessible to everyone. Each paper is transformed into a clear, plain-language overview alongside a detailed technical summary, ensuring both students and experts can grasp the latest findings without getting lost in dense jargon.
Below, you will find the most recent studies in fluid dynamics, curated and explained for a broader audience.
This paper employs a coupled Cahn-Hilliard and ALE numerical framework to establish a unified scaling law and identify an optimal cell blockage ratio () that governs the deterministic, damage-free encapsulation of hyperelastic cells in microfluidic droplets by elucidating the complex fluid-structure interactions and geometric blockage effects during droplet generation.
This paper resolves the significant variability in bedload flux measurements by deriving a universal method for determining bed shear stress that accounts for channel geometry and grain shape, successfully collapsing diverse experimental and simulation data onto a single predictive curve.
This paper introduces SympFlow, a time-dependent symplectic neural network that leverages parameterized Hamiltonian flow maps to ensure energy and momentum conservation for both modeling known systems and discovering unknown dynamics from sparse data, backed by rigorous theoretical analysis and superior performance in long-term simulations.
This paper proposes a hybrid U-Net and Fourier neural operator (HUFNO) framework that effectively combines convolutional and Fourier-based approaches to achieve highly accurate and computationally efficient large-eddy simulations of turbulent flows over periodic hills, outperforming traditional models and demonstrating strong generalization across unseen conditions.
This study demonstrates that in fluidized granular systems within narrow vertical tubes, higher sliding friction promotes amorphous (glass-like) settling structures, whereas lower friction facilitates the formation of organized (crystal-like) arrangements.
This study proposes a new framework for characterizing canopy density regimes by linking turbulence penetration to the interplay between the effective spanwise gap and the size of overlying eddies, demonstrating that traditional frontal density metrics fail to capture the physics of anisotropic layouts and Reynolds-number-dependent behavior.
This paper proposes an "embed-learn-lift" machine learning framework that utilizes nonlinear manifold learning (specifically Diffusion Maps) and Gaussian Process regression to construct minimal-dimensional surrogate models, enabling efficient numerical bifurcation and stability analysis of high-fidelity Navier-Stokes flows while preserving symmetries and outperforming traditional POD-based methods.
This paper presents a one-dimensional fluid-peridynamic structure model coupling viscous lubrication flow with a nonlocal beam theory to investigate the deformation, wave dynamics, and failure scenarios of soft-walled microchannels, revealing how nonlocal effects suppress wave propagation and identifying critical conditions for structural failure under both transient and steady hydrodynamic loads.
This paper presents an experimental investigation into how complex time-varying pitching kinematics influence dynamic stall characteristics, demonstrating the limitations of static pitch rate definitions for stall prediction and proposing modifications to the Goman-Khrabrov model to better capture nonlinear aerodynamic responses.
Using refractive index-matched stereo PIV, this study reveals that gradual () pipe expansions generate higher turbulence levels and stronger Reynolds stress anisotropy than abrupt () expansions due to geometry-induced modulation of the return flow, which sustains shear layer interaction and turbulence production in the former while confinement limits it in the latter.