995 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 membrane permeability to fluid but not solutes introduces osmotic forces that restrict the existence of canonical membrane relaxation modes and the validity of equipartition-based fluctuation predictions to a finite range of wavenumbers, which shrinks and eventually vanishes as surface tension increases.
This paper presents an end-to-end framework that combines a differentiable non-Newtonian solver with a frame-invariant tensor basis neural network to learn form-agnostic constitutive models from partial flow measurements, enabling the discovery of interpretable, geometry-portable rheological laws through automated Bayesian model selection.
This study employs the pseudopotential multi-component lattice Boltzmann method to numerically investigate the coalescence dynamics of low-viscosity liquid lenses across a wide range of contact angles, revealing quantitative agreement with experiments for small angles, validating thin-sheet theoretical models up to approximately 40 degrees, and demonstrating that initial 3D bridge growth is independent of the equilibrium contact angle.
This paper reveals that in rotating turbulence, the sign-specific conservation of helicity in fast inertial waves drives an inverse energy transfer to large-scale 2D structures, while slower modes exchange helicity across signs to sustain a forward transfer, thereby unifying the understanding of bi-directional energy fluxes across all rotation rates.
This paper introduces WAKESET, a novel large-scale dataset comprising over 4,000 high-fidelity simulations of high-Reynolds number turbulent flows during underwater vehicle recovery, designed to overcome data scarcity and advance machine learning applications in computational fluid dynamics.
This study employs Recurrence Quantification Analysis and Statistical-Spectral analysis of OH* chemiluminescence and acoustic pressure signals to extract dynamical features from mesoscale combustor flames, which are then utilized in a stacking ensemble machine learning framework to accurately classify distinct flame regimes such as stable, extinction-ignition, and propagating flames.
This paper presents a minimal mathematical model and asymptotic analysis of growing active droplets to explain how cell aggregates undergo continuous or discontinuous morphological transitions during chemotaxis, driven by exponentially small terms arising from contact line dynamics and governed by two key dimensionless parameters.
This paper presents a physics-informed graph neural network that leverages equivariant architectures and physical priors to accurately estimate hemodynamic flow fields in carotid arteries using moderately-sized in-vivo 4D flow MRI data, thereby eliminating the need for large-scale computational fluid dynamics datasets while demonstrating successful generalization to unseen vascular geometries.
This study demonstrates that increasing the specific heat capacity ratio of dispersed thermal particles in a particulate Rayleigh-Bénard system stabilizes the fluid against convection by modifying the base-state temperature profile through interphase heat exchange, thereby reducing thermal gradients near the injection wall.
This paper proposes a unified physical mechanism involving gravitational effects and pressure-induced changes in interfacial tensions within an adsorption layer to explain the size-dependent variability in sign and magnitude of droplet line tension across nanometric to millimetric scales.