1229 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 paper develops complete high-fidelity matched asymptotic expansions for velocity statistics in turbulent channels using 11 DNS datasets, validates a new a priori test confirming specific overlap forms for normal stresses advocated by recent researchers, and reanalyzes the spatial oscillations of the mean velocity logarithmic indicator function.
This paper establishes strong stability estimates for the velocity and physical densities of the two-dimensional semigeostrophic system relative to the incompressible Euler equations on a flat torus, while also proving a lifespan lower bound of that improves upon the standard hyperbolic scale.
This paper proposes a novel multi-condition physics-data coupled digital twin calibration framework that resolves flow ripple uncertainty through in-situ virtual sensing, CFD surrogate calibration, and inverse transient analysis to enable robust zero-shot compound fault diagnosis in axial piston pumps under unseen operating regimes.
This paper presents an accessible undergraduate-level laboratory experiment that demonstrates how varying the buoyancy Reynolds number influences internal wave generation and breaking, revealing three distinct turbulence regimes through linear stratification, forced topography, and advanced diagnostic techniques.
This paper introduces novel, locally computable refinement sensors based on the one-particle distribution function to enable efficient and scalable adaptive mesh and algorithm refinement for kinetic models like lattice Boltzmann methods, effectively resolving complex features in compressible, turbulent, and non-equilibrium flows.
This paper presents a robust, high-resolution Eulerian algorithm for simulating high-speed polydisperse granular multiphase flows by coupling compressible gas dynamics with mass-based moment equations closed via the generalized quadrature method of moments, demonstrating its effectiveness through various complex shock-driven numerical experiments.
By training an autoregressive conditional diffusion model on Kolmogorov flow simulations, this study reveals a state-dependent hierarchy in the predictability of turbulence extremes, demonstrating that forecast horizons are governed by the persistence of large-scale coherent structures and the lifetime of pre-extreme strain cores.
This paper demonstrates how transfer operator methods and Markov state modeling can be applied to both simulated and experimental trajectory data in stirred tank reactors to identify coherent flow structures and quantify mixing dynamics through residence and mixing time analysis.
This paper investigates how sign-indefinite helicity conservation shapes weak turbulence in rotating and odd-viscous flows by demonstrating that helical decomposition reorganizes energy cascades into sign-definite branch-specific transfers, leading to systematic backscatter and unique scale-invariant spectra validated by numerical analysis.
This paper demonstrates that odd viscosity in chiral fluids breaks the reciprocity of capillary waves, creating distinct dispersive and quasi-acoustic branches that transform standing waves into traveling waves, generate anomalous boundary layers, and induce a unique anti-Stokes drift capable of driving bulk particles opposite to the wave motion.