1210 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 generalizes Taylor dispersion theory to periodically modulated channels by deriving a rigorous long-time asymptotic expansion for passive scalar transport, which reveals a slow manifold governing algebraic decay and identifies how channel geometry and transverse velocities influence mixing timescales.
This paper presents a fast, automated CFD methodology that integrates meteorological predictions with LiDAR and cadastral data to accurately reconstruct urban airflows, achieving high validation accuracy and significantly reducing computation times for drone flight simulations compared to traditional full-landscape approaches.
This paper demonstrates that near-inertial Pollard waves modeling the Arctic Ocean's halocline become linearly unstable when their steepness exceeds a specific threshold, a condition determined by the water column's physical properties through a short-wavelength instability analysis.
This paper proposes a systematic framework utilizing four critical behavioral parameters to characterize and predict the nonlinear fluid-structure interaction dynamics between phononic materials and aerodynamic flows, bridging the gap between structural design and complex flow modulation effects.
This paper derives a systematic, higher-order Hele-Shaw approximation using the Method of Weighted Residuals to accurately model thin-gap microfluidic flows as reduced 2D equations, thereby enabling faster and more precise device design by capturing non-parabolic velocity profiles and out-of-plane effects.
This study employs scale-resolving simulations and modal analysis on infinite swept wings to demonstrate that transonic buffet arises from the superposition of quasi-2D shock oscillations and separation-driven 3D instabilities, with the latter emerging as dominant spanwise-travelling modes only when mean flow separation at the shock is sufficiently pronounced.
This paper presents an interpretable convolutional neural network framework that learns classical finite-difference operators from fluid dynamics data, effectively bridging numerical analysis and machine learning while generalizing across diverse flow conditions and data sources.
Using the Fugaku supercomputer, researchers performed a groundbreaking 100-billion-atom molecular dynamics simulation of acoustic cavitation in a simple liquid, revealing synchronized multi-bubble nucleation, growth, and fragmentation dynamics with subharmonic behavior while demonstrating that such cavitation near the horn has negligible impact on bulk acoustic properties.
This study presents a one-dimensional multifluid hydrodynamic simulation of lead and steel plate collisions in explosive welding using a Godunov-type algorithm with pressure relaxation and the Volume-of-Fluid method, successfully capturing tensile stresses and validating the unloading wave arrival time against experimental data.
This paper introduces an Asymptotic-Preserving Neural Network framework that embeds the governing physics of a multiscale viscoelastic blood flow model to reliably identify arterial wall parameters and reconstruct pressure waveforms using non-invasive Doppler ultrasound data.