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 study demonstrates that accurate stress field analysis in radial Hele-Shaw flows requires combining rheo-optical measurements with a second-order stress-optic law to account for three-dimensional stress effects that the conventional law fails to capture.
This study quantifies the theoretical global potential of surface-based atmospheric pollutant removal using natural and mechanical airflows, revealing that integrating technologies into urban infrastructure, solar farms, and HVAC systems could remove significant amounts of CO₂, CH₄, NOₓ, and PM₂.₅ at competitive costs, thereby offering a viable pathway to advance climate and public health objectives.
This paper establishes a general framework demonstrating that self-similar solutions to two-dimensional Riemann problems for the isentropic Euler system with shocks generally exhibit low regularity, specifically that the velocity field fails to belong to and may be discontinuous in the subsonic domain, thereby revealing a significantly more complex structure than solutions for potential flow.
This study develops and validates a predictive long-wave model for V-shaped filters integrated with catalytic technologies, demonstrating that while optimizing filter geometry creates a trade-off between flow rate and removal efficiency, large-scale deployment of these systems could significantly mitigate atmospheric pollution at a feasible cost.
This paper presents a comprehensive modeling framework combining asymptotic analysis and numerical methods to predict how small-scale surface textures, characterized by slip lengths, modify laminar boundary layer properties such as velocity, shear stress, and stability, thereby enabling efficient drag and transition predictions for diverse applications from microfluidics to marine transport.
This paper introduces a generalized Matrix Product State (MPS) formulation for the Lattice Boltzmann Method that enables high-fidelity, data-compressed simulations of unsteady fluid flows in complex geometries by exploiting non-local correlations to achieve compression ratios exceeding two orders of magnitude without modifying the underlying grid.
This paper uses numerical simulations of the three-dimensional incompressible Navier-Stokes equations to demonstrate that Kelvin waves in classical viscous vortex filaments align with Lord Kelvin's predictions, while also revealing the existence and collision dynamics of solitons and proposing a feasible experimental method for their generation.
This paper investigates the evolution of two-dimensional incompressible Navier-Stokes solutions initialized as polygonal vortex crystals, with or without a central vortex, by leveraging symmetry and stability to characterize their behavior up to sub-diffusive time scales before vortex merging occurs.
This study investigates the rheological properties and shear-induced structural transitions of three ferroelectric nematic liquid crystals, revealing distinct shear-rate-dependent viscosity behaviors, flow-alignment regimes, and the unique tendency of the polarization vector to remain parallel to the shear direction to avoid splay deformations.
This paper proposes CoK-PCA, a dimensionality reduction method based on the co-kurtosis tensor that outperforms traditional PCA in accurately capturing stiff chemical dynamics and extreme-valued ignition events in combustion datasets by better identifying critical directions in the thermo-chemical state space.