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 paper proposes FISR-EQL, an interpretable framework that embeds equation learning into a PDE-constrained field inversion process to derive compact, physics-consistent analytical corrections for turbulence models, achieving performance comparable to neural networks while significantly improving separated flow predictions without sacrificing transparency.
This study analyzes ultra-dilute polymer solutions in Navier-Stokes turbulence at a Weissenberg number of approximately 80, revealing that chains predominantly stretch as material lines in axisymmetric biaxial extension regions while exhibiting non-Gaussian Lyapunov exponent statistics, synchronization across trajectories, and a distinct alignment pattern where the second strain-rate eigenvector significantly contributes to compression.
This study characterizes the deformation and instability of sessile soap bubbles in a parallel-plate electric field, revealing a stable spheroidal regime governed by a single steady-state branch that transitions into a conical instability with a half-angle of approximately 30 degrees, followed by pre-jet dynamics well-described by an inertia-capillary model.
This paper presents and validates a sharp-interface Volume-of-Fluid method for simulating phase-change on unstructured polyhedral meshes, demonstrating its ability to eliminate grid-induced anisotropy and accurately model complex flows like turbulent boiling without relying on empirical closure models.
This paper demonstrates that turbulent circulation fluctuations in homogeneous and isotropic turbulence can be accurately modeled using a superstatistical framework based on q-exponentials, linking the dissipation field to small-scale vortices and opening new avenues for understanding turbulence through non-extensive statistical mechanics.
This study demonstrates that for Herschel-Bulkley viscoplastic ligaments at low Ohnesorge numbers, shear-rate-dependent rheology enables two distinct mechanisms—vorticity detachment in shear-thickening fluids and curvature-induced pressure gradients in shear-thinning fluids—to prevent end-pinching and facilitate inertial-capillary reopening, thereby challenging the Newtonian assumption that break-up is the inevitable outcome in the inviscid limit.
This paper demonstrates that biomimetic substrates with overlapping fish-scale architectures can exhibit programmable deterministic chaos through geometric design, where unilateral contact, progressive jamming, and asymmetric texturing drive a period-doubling cascade into chaotic flexural vibrations without requiring large deflections or material nonlinearity.
This study employs a systematic computational search using variational optimization to identify initial conditions that maximize norms relevant to the Ladyzhenskaya-Prodi-Serrin regularity criteria, revealing that while extreme 3D Navier-Stokes flows exhibit growth rates consistent with finite-time singularity formation, they ultimately fail to sustain this growth long enough to actually become singular.
This paper introduces AeTHERON, a physics-informed heterogeneous graph neural operator that leverages a dual-graph architecture and sparse cross-attention to efficiently and accurately model complex fluid-structure interactions in flapping flexible fins, achieving high-fidelity temporal extrapolation with significantly reduced computational costs compared to traditional direct numerical simulations.
This paper proposes and validates an improved third-order scheme for pseudopotential lattice Boltzmann models that effectively suppresses spurious velocity oscillations at phase interfaces without adding computational complexity, thereby ensuring more reliable simulations of multiphase flows.