1255 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 a novel stability criterion for incompressible shear flows that combines input-output analysis with the small-gain theorem to establish explicit thresholds on disturbance magnitudes, demonstrating that structured nonlinear models provide stability predictions consistent with experimental and simulation data across various canonical flows and Reynolds numbers.
This study investigates the destabilization and fragmentation of a radially expanding liquid rim after it is severed from its fluid source, revealing that the resulting ballistic rim breaks up via ligaments and corrugations with timescales and counts predicted by unsteady sheet theories, while also analyzing the subsequent re-formation of the rim.
This study reveals that the free decay of quasi-two-dimensional superfluid turbulence in nanofluidic channels follows a universal transient before entering a slower, geometry-dependent regime, a behavior driven by the interplay between vortex pinning on disordered walls and probe-induced mobilization and successfully reproduced by a numerical model incorporating velocity-dependent mutual friction.
This paper resolves the discrepancy between Kazantsev theory and numerical simulations regarding small-scale dynamo decay at small Prandtl numbers by demonstrating that the observed exponential decay is a temporary effect caused by large-scale velocity correlator flattening, which corresponds to a long-living virtual level in the associated Schrödinger-type equation.
This paper presents a generalized inner product-based method using self-adjoint operator theory to model the time-domain evolution of underwater pressure disturbances caused by events like explosions or volcanic eruptions, revealing that while static compression has a small but non-negligible effect on the resulting acoustic-gravity wave propagation.
This study experimentally and numerically investigates the dynamics of high-speed liquid jets generated by the interaction of two tandem cavitation bubbles, identifying three distinct jet regimes governed by the spatiotemporal impact of the first bubble's collapse pressure wave and establishing phase diagrams to guide biomedical applications like needle-free injection.
This paper investigates the impact of turbulence on hydroacoustic waves, revealing that while temperature effects are negligible, turbulence induces periodic frequency-dependent phase shifts and amplitude variations (including six distinct decay patterns), ultimately suggesting that the interaction constitutes a process of stimulated absorption and emission in water.
This paper proposes a new five-term nonlinear reduced-order drag model that incorporates both linear and quadratic coupling with the lift coefficient to accurately reproduce drag signals in cylinder wakes where traditional two-to-one frequency assumptions fail under harmonic excitation.
This study bridges the long-standing Prandtl number gap in 3D simulations of thermohaline convection by demonstrating that the chemical mixing model of Brown, Garaud, & Stellmach (2013) remains valid across stellar regimes down to , thereby ruling out the Prandtl number discrepancy as the cause of tensions between the model and astronomical observations.
This study employs direct numerical simulations and compares four interpretable data-driven models—DMD, Hankel DMD, SINDy, and Stochastic Langevin regression (SLR)—to decode the interfacial dynamics and acceleration of a turbulent binary fluid droplet, demonstrating that SLR offers the most accurate and computationally efficient approach for generalizing physical properties like surface tension and droplet size.