1272 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 demonstrates that applying a wavy-wall geometry to the suction side of a NACA4412 airfoil at Re_tau = 3000 significantly delays turbulent separation and increases the friction coefficient by up to 42.3% by enhancing small-scale streamwise convection and sweeping motions, provided the geometry avoids inducing detrimental large-scale flow separations.
This study demonstrates that engraving vertical grooves on condensing plates can transform the inherently stochastic process of edge dripping into a spatially organized and temporally regular release mechanism by redirecting surface flow into geometry-defined drainage paths, thereby enabling precise control over water detachment for applications in dew harvesting and passive cooling.
This paper provides a rigorous mathematical justification for damped-driven wave turbulence theory by proving that the stochastic dynamics of the nonlinear Schrödinger equation converge to a deterministic kinetic equation under specific scaling limits, thereby establishing a formal framework for the turbulent energy cascade observed in empirical studies.
This paper presents a physics-informed detection framework that overcomes the invisibility limitation of refractive index matching by locating transparent spheres within tomographic data, thereby enabling the first direct calculation of drag and lift histories on freely moving bodies through simultaneous analysis of velocity, pressure, and wake structures.
This paper presents an adaptive sampling framework that couples a classifier network with a deep generative model (KRnet) to efficiently detect hydrodynamic bifurcation boundaries by iteratively concentrating computational resources in high-uncertainty regions, thereby significantly reducing the number of required Navier-Stokes simulations.
This paper proposes a distributed Physics-Informed Neural Network framework utilizing spatiotemporal domain decomposition, reference anchor normalization, and CUDA-accelerated training to achieve scalable, high-fidelity flow reconstruction while resolving pressure indeterminacy and computational bottlenecks.
This paper demonstrates that a stochastic Lorenz system serves as a faithful low-dimensional surrogate for mean-wind reversals in Rayleigh-Bénard convection, revealing that the non-Gaussian, multifractal statistics of lobe-switching times arise from multiplicative intermittency characteristic of turbulence.
This paper presents a data-driven platform using Physics-Informed Neural Networks (PINNs) embedded with the nonlocal granular fluidity (NGF) model to accurately solve forward granular flow problems and infer key material parameters, such as the nonlocal amplitude, from sparse experimental observations where traditional local models fail.
This paper presents numerical results showing that while a free swirling jet driven by an azimuthal body force can amplify magnetic fields, the resulting instability is convective rather than self-sustaining, necessitating specific modifications to achieve a working laboratory dynamo.
This study combines experiments and numerical simulations to demonstrate that nanosecond laser impacts on free-falling liquid tin droplets generate singular jets with velocities up to ten times the impact speed, a phenomenon driven by the interplay between radial flow and droplet curvature during retraction and governed by the impact Weber number and laser pressure width.