1247 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 investigates unsteady separated flow over a three-dimensional Gaussian bump at a Reynolds number of , identifying four distinct broadband phenomena and revealing that the very-low-frequency spanwise meandering of the wake is dynamically coupled with the streamwise stretching of the separation zone.
This study demonstrates that a machine learning-based mesh movement approach (UM2N) integrated into the Thetis software significantly accelerates and robustly enhances the accuracy of non-hydrostatic tsunami simulations for probabilistic coastal hazard assessment.
This study presents a robust quantitative framework combining Mach-Zehnder interferometry with humidity-controlled confinement to precisely map the drying kinetics and internal concentration fields of water-glycerol droplets, successfully validating a diffusion-controlled evaporation model and extracting concentration-dependent transport properties while confirming that mass diffusion dominates over buoyancy-driven convection.
This study introduces a factorized-implicit Fourier Neural Operator (F-IFNO) framework that enhances long-term stability and accuracy in predicting three-dimensional turbulence by integrating uncertainty quantification and error propagation analysis to overcome the limitations of traditional models and existing neural operators.
This paper presents a quadrature-based model reduction framework for Lagrangian hydrodynamics that utilizes a strongly energy-conservative variant of the empirical quadrature procedure to achieve near machine-precision total energy conservation while maintaining accuracy comparable to standard methods.
This study reveals that the rupture of micron-thick liquid films is governed by a deterministic double-threshold mechanism requiring both sufficient outward driving force and cavity distortion, which explains why these films perforate despite molecular forces being negligible at that scale.
This paper proposes new Van Driest-type and semi-local-type temperature transformations for compressible turbulent channel flow, derived from momentum and energy balance analyses, which successfully recover the incompressible law of the wall with high accuracy by accounting for mixing length effects, body force work, and turbulent kinetic energy flux.
This paper investigates how linear Ekman friction alters the enstrophy cascade in two-dimensional turbulence by demonstrating that, under high friction, vorticity becomes passively transported, allowing a phenomenological model based on Gaussian-distributed Lagrangian Finite Time Lyapunov Exponents to accurately predict the resulting spectral slope corrections.
This study investigates the similarities and differences between velocity and passive scalar scale-by-scale equilibria in turbulent channel flow with , revealing that while both fields achieve Kolmogorov equilibrium at a specific length scale below the inertial range, the characteristics of this equilibrium and the nature of their interscale transfer rates exhibit distinct Prandtl number dependencies and alignment behaviors.
This paper introduces an SVGP-KAN framework that reconstructs time-resolved flow fields from sparse velocimetry data with accuracy comparable to classical methods while providing well-calibrated epistemic uncertainty estimates to guide experimental design.