995 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 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 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 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.
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 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 presents and validates a robust recursive regularised lattice Boltzmann method for incompressible magnetohydrodynamics that utilizes a double-distribution formulation and fourth-order Hermite expansion to enhance numerical stability, reduce lattice-dependent artifacts, and eliminate the need for explicit velocity gradient calculations.
This paper presents a machine learning-assisted adjoint-based shape optimization framework that utilizes a Conditional Variational Autoencoder to surrogate a complex Voith Schneider Propeller, enabling efficient ship hull designs that achieve over an 8% resistance reduction while avoiding the prohibitive computational costs of full transient propulsion simulations.
This paper formulates and solves the brachistochrone problem for bodies moving through dense fluids by incorporating buoyancy, viscous drag, and added mass effects, revealing that the classical cycloid becomes suboptimal or unreachable as body density approaches fluid density and establishing a critical framework for planning short-range trajectories of buoyancy-driven underwater vehicles.
This study combines micro-CT and time-resolved X-ray radiography to reveal that needle-punch intensity enhances through-thickness liquid transport in nonwoven felts by creating preferential flow pathways, despite reducing single-phase permeability, thereby establishing a framework for optimizing liquid dynamics in opaque fibrous materials.
This paper establishes a three-dimensional dynamical-systems framework for passive gliding that identifies a terminal velocity manifold and a separatrix surface to explain how bio-inspired airfoils achieve robust, efficient glides across diverse initial conditions by partitioning phase space into distinct descent behaviors.