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.
This study combines advanced data reconstruction techniques with non-time-resolved PIV to demonstrate that the symmetry of a flexible plate's oscillation in normal flow dictates its wake topology, revealing that antisymmetric vibrations induce a classic 2P vortex shedding pattern and an additional mean drag penalty compared to the symmetric 2S mode.
This study demonstrates that soluble surfactants suppress hydrodynamic coarsening in bicontinuous liquid-liquid phase separation primarily through Marangoni stresses rather than reduced interfacial tension, with the inhibition peaking at an intermediate Péclet number due to an optimal balance between surfactant replenishment and gradient retention.
This paper introduces LCS.jl, a high-performance, multi-platform Julia-based simulation model for turbulent particle-laden flows that leverages GPU-native algorithms to achieve superior scalability, portability, and up to 18x speedup over CPU implementations while maintaining strong agreement with established fluid and particle statistics.
This paper demonstrates that polymeric turbulence acts as a less efficient mixer than Newtonian turbulence, characterized by small, interspersed patches of strong fluctuations with smoother boundaries and reduced average scalar flux despite higher local fluctuation intensity.
This paper revisits the Schrödinger-Navier-Stokes formulation of classical fluids to propose a novel quantum algorithm based on tensor-network Carleman embedding of the Hamilton-Jacobi equations, which overcomes dissipator challenges and demonstrates convergence for Kolmogorov-like flows in a classical emulation.
This study demonstrates that the pinch-off of density-matched non-Brownian rod suspensions reveals a continuum breakdown governed by rod length rather than diameter, leading to an effective extensional viscosity that increases with both volume fraction and aspect ratio while following a modified scaling law for spherical particles.
This paper introduces a signal-aware conditional denoising diffusion probabilistic model that accurately predicts transonic wing pressure distributions on unstructured NASA Common Research Model data by leveraging principal component representation and a timestep-dependent loss weighting to better capture sharp nonlinear features like shock waves and suction peaks compared to deterministic baselines.
This paper introduces Scale-Autoregressive Modeling (SAR), a hierarchical generative approach that samples fluid flow distributions from coarse to fine resolutions to achieve faster inference and higher accuracy than state-of-the-art diffusion and flow-matching models while avoiding the error accumulation of traditional time-stepping surrogates.
This study utilizes direct numerical simulations at Mach 2.5 to investigate compressible turbulent boundary layers over square-rib roughness under adiabatic and cooled conditions, proposing a fitting-based optimization for virtual origin determination, demonstrating the superiority of the GFM transformation over van Driest, and formulating a modified rough-wall Generalized Reynolds Analogy to address the breakdown of classical analogies caused by the disparity between momentum drag and heat transfer mechanisms.
This study demonstrates that the apparent separation between quasi-2D and 3D regimes in rotating turbulence is an artifact of finite vertical measurement windows rather than an intrinsic flow property, thereby challenging the validity of pure 2D manifold theories and highlighting the need for resolution-aware frameworks.