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.
NORi is a novel, physics-based machine learning parameterization that combines neural ordinary differential equations with a Richardson number-dependent closure to accurately and stably simulate ocean boundary layer turbulence and entrainment dynamics in climate models, outperforming traditional methods while requiring minimal training data and ensuring long-term numerical stability.
This paper derives improved analytical criteria for the inviscid stability of axisymmetric flows in pipes and annuli by establishing a refined sufficient condition for stability and a novel condition for instability, both of which effectively predict neutral parameters verified by eigenvalue computations.
This study demonstrates that while the magnetic Prandtl number significantly influences reconnection rates in the Sweet-Parker regime, this dependence weakens considerably in the fully plasmoid-mediated regime where rates become nearly independent of the Prandtl number, a finding that helps reconcile discrepancies with boundary-driven Taylor problem simulations.
This study utilizes direct simulation Monte Carlo (DSMC) simulations to demonstrate that prescribed wall heat flux in rarefied micro-nozzles governs flow behavior through coupled wall-bulk thermal responses, where strong heating induces wall-bulk stratification and aerodynamic blockage that reduces mass flow but significantly enhances specific impulse by augmenting thermal and pressure thrust.
This paper introduces HiLiftAeroML, the first open-source high-fidelity CFD dataset featuring 1,800 GPU-accelerated LES simulations of NASA's CRM high-lift geometry, designed to accelerate the development of AI surrogate models for aerospace applications.
This paper introduces ELGIN, a physics-informed graph neural network surrogate that significantly accelerates and improves the accuracy of predicting turbulent nanoparticle dispersion in dental clinics compared to traditional CFD simulations, enabling near real-time infection-risk screening.
This paper introduces a unified matched eigenfunction expansion method (MEEM) framework for generalized concentric bodies that demonstrates significantly faster convergence and smaller matrix sizes compared to traditional boundary element methods, while maintaining high accuracy for both vertical and slanted geometries.
This study demonstrates through numerical simulations and analytical modeling that a solid particle induces universal, self-similar pinch-off dynamics in stretching liquid ligaments, where the subsequent breakup becomes independent of particle size and is governed by the interplay between ligament stretching and Rayleigh-Plateau instability.
This paper extends a kinetic closure of turbulence by developing a theoretical framework that addresses the non-Markovian collision dynamics and unresolved subgrid equilibrium in filtered Boltzmann equations through a Chapman--Enskog analysis, ultimately validating the resulting BGK-like closure against lattice Boltzmann simulations and traditional models.
This study reveals that parity under sign reversal acts as a fundamental organizing principle in homogeneous isotropic turbulence, where odd-odd velocity-gradient correlations exhibit universal scaling due to sign decorrelation, while even-even correlations display distinct, intermittency-driven scaling exponents directly linked to the fractal geometry of intense gradient structures.