1229 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 demonstrates that periodically textured microchannel walls can passively align elongated microparticles along the centerline through geometry-driven shear gradients, offering a robust framework for designing microfluidic devices to sort or focus anisotropic particles across various flow regimes.
This study demonstrates that at high Reynolds numbers, time-varying wind-turbine wakes propagate as nonlinear traveling waves that can be accurately described by a quasi-steady Lagrangian transformation, revealing that wake advection is critical for wind-farm modeling and that time-varying control can optimize farm performance even under nominally steady conditions.
This study demonstrates that while abrupt and gradual axisymmetric pipe expansions share similar mean flow topologies and convection speeds, they fundamentally differ in the spatial organization and persistence of coherent structures, with the abrupt step promoting stronger spectral concentration and segmented material transport compared to the broader, less fragmented deformation regions of the gradual wedge.
This study utilizes Direct Numerical Simulations with realistic salt diffusivity to demonstrate that buoyancy-driven convection remains the dominant mechanism for ice-ocean boundary turbulence even at near-horizontal slopes, with external shear only significantly influencing melt rates when flow speeds exceed 5 cm/s.
This paper presents a physics-informed neural network framework with adaptive weighting and dynamic collocation strategies to enable rapid, mesh-free forward and inverse modeling of fluid flow in dual-porosity/permeability porous media, offering robust parameter identification and accurate handling of complex geometries and solution discontinuities.
This paper presents a graph neural network (GNN) that accurately predicts filtered species production rates for large-eddy simulations of turbulent premixed flames on complex, non-uniform meshes, demonstrating superior generalization across varying fuel compositions and filter widths compared to traditional unclosed models and convolutional neural networks.
This study demonstrates that the Gouy phase shift during the focusing of purely compressive shock waves can generate localized negative pressure and induce homogeneous cavitation within a sub-millimetric droplet without external rarefaction, offering a novel strategy to enhance the safety and precision of biomedical acoustic treatments.
This paper presents a two-dimensional mathematical model and numerical simulations demonstrating that increasing volumetric heat flux enhances thermocapillary flow, thereby reducing the fraction of colloidal particles captured to form clusters during liquid film evaporation in an unevenly heated cell.
This study develops and validates high-accuracy, real-time CNN-based surrogate models trained on CFD data to predict Nusselt number distributions in flexible impinging jet arrays with dynamic inlet/outlet configurations, enabling efficient thermal management and model-based control strategies.
This paper presents a computationally efficient, uncertainty-aware sequential data assimilation framework that utilizes an ensemble Kalman filter operating within a physics-augmented latent space to accurately reconstruct disturbed aerodynamic flows and loads from sparse surface pressure measurements during severe gust encounters, while also demonstrating robustness to sensor failures.