989 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 demonstrates that additively manufactured, optimized perforated acoustic black hole dampers serve as a robust, broadband passive solution for effectively mitigating thermoacoustic instabilities in hydrogen-fueled combustors across various operating conditions.
By combining analytical modeling, lattice Boltzmann simulations, and X-ray experiments, this study elucidates the critical Bond number and confinement-dependent mechanisms governing bubble clogging, unclogging, and coalescence in highly porous media relevant to electrochemical devices.
This paper characterizes families of solitary waves in a coupled Korteweg--de Vries and linear Schrödinger system by analyzing a sequence of pitchfork bifurcations from uncoupled KdV solitons, proving that the ground state solution is an energy minimizer and connecting these bifurcations to known exact solutions.
This study utilizes direct numerical simulations to demonstrate that the distribution of intense spectral energy transfers in homogeneous isotropic turbulence is primarily determined by the proximity to energy-containing scales rather than the local or nonlocal nature of triadic interactions, a finding that aligns with EDQNM theory and the forward energy cascade picture.
This paper demonstrates through direct numerical simulations that incorporating helicity effects alongside Smagorinsky-like eddy viscosity improves subgrid-scale modeling in large-eddy simulations by addressing the over-dissipative behavior of standard models.
This paper presents a minimal mean-field elastohydrodynamic model that couples contact mechanics and lubrication to theoretically characterize frictional transitions along the Stribeck curve, deriving asymptotic expressions for friction in boundary, mixed, and hydrodynamic regimes and generalizing the classical Stribeck curve into a multidimensional phase diagram governed by dimensionless speed, load, and surface roughness.
This paper presents a physics-guided, differentiable correlation for predicting the laminar flame speed of methane-hydrogen-air mixtures under varying dilution conditions, offering accuracy comparable to machine learning models while ensuring physical consistency and robust extrapolation for use in computational fluid dynamics and fuel-flexible combustion control.
This paper investigates the stationary sliding and dynamic behaviors of compound drops composed of two immiscible liquids on an inclined substrate using a mesoscopic hydrodynamic model, analyzing how their configuration and velocity depend on inclination, volume ratio, and viscosity ratio while also exploring time-periodic fusion-overtaking-splitting dynamics beyond the stationary regime.
This paper establishes a sufficient stability condition for nonlinear dissipative partial differential equations by deriving an explicit inequality linking linear dissipation, quadratic nonlinearity, and external forcing, and demonstrates its applicability to fluid dynamics models like the Burgers, KPP-Fisher, and Kuramoto-Sivashinsky equations.
This paper presents a novel, fully meshless approach for reconstructing continuous velocity fields from scattered flow data by integrating gradient-informed adaptive sampling, anisotropic basis functions, and soft constraints to significantly improve accuracy and physical consistency in regions with sharp gradients while reducing computational cost.