967 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 numerically investigates the stability of in-line flapping plates in an inviscid fluid, identifying quantized equilibrium schooling modes that can destabilize via downstream-propagating oscillations but are successfully stabilized through a simple relative-velocity-based control mechanism that also regularizes the wake vortex pattern.
This study employs a biglobal stability framework to demonstrate that side-wall wetting exerts a dual influence on falling film stability, acting as a relative destabilizing mechanism in confined channels by weakening boundary-layer stabilization, while simultaneously providing significant long-wave stabilization in weakly-confined channels through enhanced capillary anchoring.
This paper extends the study of self-similar rupture in thin liquid films to non-Newtonian power-law fluids, revealing a complex bifurcation structure with snaking behavior near the Newtonian limit and an infinite set of solutions in the extreme shear-thinning regime, while numerical simulations confirm that time-dependent dynamics are attracted to a single primary similarity solution branch.
This paper theoretically demonstrates that a homogeneous, straight elastic filament can spontaneously achieve self-propulsion through a buckling instability that breaks symmetry, leading to distinct nonlinear swimming modes such as steady translation, metastable rotation, or oscillation depending on its flexibility.
This paper presents a hybrid turbulence model that corrects the underprediction of turbulent kinetic energy by using Physics Informed Neural Networks to improve turbulent diffusion modeling and Neural Networks to recalibrate model coefficients, achieving excellent agreement with DNS data across various flow configurations while offering a pathway to implement the results in commercial CFD codes via symbolic regression.
This paper proposes a data-driven framework combining information-theoretic machine learning, convolutional neural networks, and autoencoders to extract interpretable, time-varying vortical structures and their causal relationships with aerodynamic coefficients from snapshot data across diverse unsteady flow scenarios.
This paper derives exact analytical solutions for the flow and pressure fields generated by monopole and dipole singularities in a compressible thin fluid layer with odd viscosity, providing critical insights into the hydrodynamic interactions and collective behavior of microswimmers in chiral active fluids.
This study reveals that hydrodynamic interactions, previously assumed negligible in semi-dilute regimes, drive a collective cascade of tumbling events in sheared colloidal rod suspensions that disrupts flow alignment and significantly increases viscosity, necessitating a revision of existing constitutive models.
This study utilizes DSMC simulations to demonstrate that rarefaction-induced inflation of hypersonic bow shocks over a circular cylinder is a coupled compression-relaxation process involving multi-scale changes in macroscopic and internal-energy fields, rather than a simple geometric rescaling of a continuum-like shock layer.
This paper presents the implementation, validation, and astrophysical benchmarking of a high-order ADER-DG solver for compressible Euler equations within the ExaHyPE framework, demonstrating its ability to accurately resolve complex flow features like shocks and interfaces through a combination of adaptive mesh refinement and a posteriori subcell limiting.