967 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 proposes two variational quantum circuit architectures, R1 and R2, to train quantum machine learning models that accurately approximate the nonlinear collision operator in the quantum lattice Boltzmann method for both continuous multi-step evolution and single-step high-precision reconstruction.
This study utilizes high-speed microscopy to demonstrate that viscoelasticity destabilizes the receding contact line of sliding drops, triggering filament formation, with the effect critically dependent on polymer charge due to distinct wetting properties.
This paper analyzes the roll instability of fish-like underwater robots by modeling them as a hydrodynamic Chaplygin sleigh, demonstrating that their periodic yaw motion induces parametric roll excitation described by a nonhomogeneous Mathieu equation, which reveals a fundamental trade-off between swimming speed and roll stability.
This paper analytically proves the existence of internal wave Whispering Gallery Modes (WGMs) in channels using continuous symmetries, identifies a new along-channel critical-slope wave attractor that positions WGMs at the boundary between attraction basins, and applies these findings to explain energy fluxes in submarine canyons and tidal intensification near critical slopes.
This paper demonstrates that in magnetized stellar cores, nonaxisymmetric internal gravity waves convert into slow-magnetosonic waves that resonate with Alfvén waves and undergo rapid damping via phase mixing, thereby providing a mechanism for the suppression of global oscillation modes observed in stars.
This paper presents a multidimensional, vertically integrated modeling framework that incorporates phase change to simulate the formation and expansion of aquifers within cold firn, revealing how lower initial temperatures impede lateral propagation through porosity reduction and freezing, thereby offering new insights into subsurface meltwater storage's role in sea-level rise.
This paper proposes a space-dependent eddy thermal diffusivity model to derive analytical mean temperature profiles for turbulent vertical natural convection, revealing universal scaling functions in inner and outer regions that align well with direct numerical simulation data.
This paper proposes a physics-enhanced 3D neural field framework that outperforms traditional surrogate models in efficiently and accurately predicting steady hypersonic flow around the Orion reentry capsule by capturing sharp discontinuities and enforcing physical boundary conditions.
This paper introduces a sparse convex-relaxation framework using a Müntz–Szász/Jacobi dictionary to estimate effective local scaling exponents from short, boundary-anchored velocity profiles, demonstrating its utility as a finite-scale geometric diagnostic that reveals directional anisotropy and vorticity-aligned roughness structures in turbulent flows without requiring external calibration.
This paper introduces "The Closure Challenge," a standardized open-source benchmark comprising curated datasets, evaluation code, and specific test cases designed to establish a common metric for evaluating and advancing machine learning models in Reynolds-averaged Navier-Stokes turbulence modeling.