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 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.
This paper introduces a combined dynamic-kinematic validation framework and a novel diagram to demonstrate that relying solely on maximum spreading diameter is insufficient for accurate droplet impact modeling, advocating instead for a hybrid contact angle model that better captures both geometric spreading limits and internal kinematic receding dynamics.
This study investigates buffet dynamics on an Airbus XRF-1 configuration caused by ultrahigh-bypass-ratio nacelle installation at Mach 0.84, utilizing delayed detached eddy simulations and unsteady pressure-sensitive paint measurements to identify dominant shock-boundary-layer interaction modes characterized by wave-like shock motions and spanwise flow oscillations.
This paper presents a fluctuating lattice Boltzmann formulation based on orthogonal central moments that introduces stochastic forcing directly in the central moment space to exactly satisfy the fluctuation-dissipation theorem, ensuring thermal equilibrium, Galilean invariance, and enhanced numerical stability even in the over-relaxation regime.
The paper introduces WindDensity-MBIR, a model-based iterative reconstruction algorithm that formulates wind tunnel wavefront tomography as a Bayesian sparse-view problem to accurately estimate 3D turbulent density fields from limited and sparse data, achieving high-fidelity recovery even under challenging conditions like small fields of view and removed wavefront modes.
This paper demonstrates that the complex, high-dimensional dynamics of turbulent Rayleigh-Bénard convection, including rare flow reversals, can be accurately captured in a compact 20-dimensional latent space by employing a multiscale framework that explicitly separates and models slow and fast temporal components.
This paper introduces a kinetic closure for the filtered Boltzmann-BGK equation that naturally incorporates turbulent subfilter stresses and diffusion without requiring scale separation or explicit modeling, demonstrating improved stability and reduced dissipation in lattice Boltzmann simulations compared to the Smagorinsky model.
This paper introduces the -criterion, a novel and computationally efficient Eulerian method that objectively identifies coherent vortices from instantaneous flow data by isolating genuine swirling dynamics from rigid-body motion, thereby overcoming the limitations of existing local and Lagrangian approaches.
This paper presents a real-time, interpretable surrogate model for predicting the heave dynamics of a sphere near a wall by combining Sparse Identification of Nonlinear Dynamics (SINDy) to extract governing ODEs from CFD data with a neural operator network that maps geometric parameters to these dynamics.
This paper experimentally demonstrates that large-scale hydroelastic turbulent waves, initially in a state of statistical equilibrium, undergo free decay following a power-law energy dissipation driven by linear viscous damping, a theoretical prediction that aligns closely with experimental data across various initial conditions.