1126 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 a parallelized, finite-volume micro-macro kinetic flux-vector splitting scheme for the multidimensional Boltzmann-ES-BGK equation that reduces computational cost by combining a fluid model with a projected kinetic correction, while correctly capturing transport coefficients and preserving compressible Navier-Stokes asymptotics across various Knudsen numbers.
This study combines microfluidic experiments, theory, and simulations to demonstrate that the orientation dynamics of rigid fibers in a Burgers-like vortex are accurately described by Jeffery equations, revealing a decoupled behavior where fibers uniformly precess due to vorticity while aligning with the vortex axis via strain, even in the presence of finite particle size and inertia.
This study develops a fully coupled transient numerical framework to investigate how substrate curvature, wettability, and thermal conductivity govern the evaporation dynamics, Marangoni-driven internal circulation, and temporal evolution of capillary adhesion forces in liquid bridges between curved solid surfaces.
This paper demonstrates that passive hydrodynamic feedback between viscous flow and elastic fiber deformation can create fluidic hysterons, enabling the construction of memory networks that transition from non-interacting return point memory to avalanche-like switching through geometric control.
This study utilizes direct numerical simulations of fully compressible reactive Navier-Stokes equations with detailed chemistry to demonstrate how wall heat losses and geometric confinement jointly influence early-stage flame propagation and the formation of tulip flames in hydrogen-air combustion within confined channels.
This paper presents a theoretical framework for diffusio-osmotic flow in long axisymmetric channels with thin electrostatic diffuse layers, demonstrating that while the flow rate in a cylinder matches that of an equivalent slit, variable channel geometries can significantly enhance or retard the flow and tune ionic flux, enabling a simplified cylinder approximation for designing micro- and nanofluidic devices.
This study enhances deep learning models for ammonia/natural gas combustion kinetics by introducing physics-aware data augmentation and scale separation techniques, achieving high-fidelity predictions with up to a 20x speedup in CFD simulations to overcome the computational bottlenecks of stiff chemical ODEs.
This paper presents a stable, symmetry-exploiting numerical method using truncated Hamiltonian formulations to compute and analyze the bifurcations, complex patterns, and instability mechanisms of three-dimensional gravity-capillary standing waves, demonstrating excellent agreement with full potential-flow models.
This study investigates the conversion between kinetic and surface energy in periodically forced multiphase turbulence through direct numerical simulations and the development of an enhanced total-energy model that successfully captures non-equilibrium phase lags and system dynamics across various flow regimes.
This paper presents a thermodynamically consistent neural network trained on high-resolution convection data to model non-equilibrium moist phase exchanges within a discontinuous Galerkin atmospheric model, demonstrating its ability to simulate sub-km resolution three-phase cloud formation compared to traditional equilibrium-based physics.