1169 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.
The paper introduces HydroFirn, an efficient large-scale multidimensional numerical model for firn hydrology that overcomes the limitations of traditional one-dimensional approaches by simulating coupled unsaturated-saturated flows and dynamic ice layer formation, thereby improving the understanding of meltwater percolation and reducing uncertainties in sea-level rise estimates.
This study establishes that strain is the critical control parameter governing the transition from sedimentation to full suspension in dense, non-Brownian particle systems under both steady and oscillatory shear, enabling the development of a predictive model and unified state diagram for resuspension thresholds across diverse flow conditions.
This paper presents three-dimensional direct numerical simulations of turbulent Rayleigh-Bénard convection in a rectangular box to demonstrate how a stable large-scale circulation fixes plume ejection regions, revealing that while local thermal and viscous dissipation rates and boundary layer thicknesses vary significantly with plume activity, the global heat transport laws remain consistent with other low-to-moderate aspect ratio configurations.
This paper proposes a data-driven framework that utilizes autoencoders and neural networks to construct a reduced-order oscillator model capable of accurately forecasting the long-term multi-frequency dynamics of high-dimensional turbulent flows, overcoming previous limitations in handling chaotic, multi-frequency characteristics.
This paper demonstrates that the Schrödinger-Navier-Stokes equation is formally equivalent to the Navier-Stokes-Korteweg equations for capillary fluids, deriving its dispersion relations and proposing its utility for modeling microfluidic systems and quantum simulations of complex flowing matter.
This paper derives a universal shape correction coefficient for the electrophoretic mobility of nearly spherical particles at arbitrary Debye lengths, revealing that only the quadrupolar () component of surface deformation influences mobility at leading order while higher harmonics remain silent, and explicitly acknowledges the use of AI-assisted code generation in the research process.
This study numerically demonstrates that the length, shape, and stiffness of bicuspid valve leaflets critically determine their efficiency in preventing retrograde flow, explaining why shorter leaflets in abnormal or immature valves lead to reflux.
This study demonstrates that while finite temperatures can completely quench particle transport over high potential barriers at intermediate ranges for both Langevin and Basset-Boussinesq-Oseen (BBO) dynamics, hydrodynamic memory in BBO systems uniquely mitigates this effect by sustaining initial momentum, thereby enabling transport even in regimes where thermal fluctuations would otherwise halt it.
This study demonstrates through nematohydrodynamic simulations that solute dispersion in confined active nematic fluids across both oscillatory and dancing pre-turbulent regimes is driven by velocity field second moments proportional to activity, significantly enhancing diffusion rates with potential applications in biological and engineered systems.
This paper demonstrates that optimized single-precision simulations on consumer-grade GPUs can achieve accuracy comparable to double-precision methods while delivering a 27-fold speedup, enabling efficient large-scale modeling of complex nematohydrodynamic systems through the implementation of a shifted distribution function and an optimal finite-difference time step.