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 proposes a novel, stable, and accurate semi-implicit lattice Boltzmann method with a centered coupling scheme to solve Biot's consolidation model for linear poroelasticity, effectively overcoming the instabilities of naive coupling approaches and capturing discontinuous solutions in strongly coupled systems.
This paper analytically derives the growth rates of the linear Rayleigh-Taylor instability in foams by modeling their elastic and plastic phases, revealing that the foam's microstructure can stabilize certain wavelengths and that homogeneous models tend to overestimate growth, with implications for inertial confinement fusion and broader scientific fields.
This paper presents a physics-informed convolutional neural network framework that accurately predicts pore-scale velocity fields in complex porous media by integrating physical constraints into the training process, thereby enabling significant acceleration of Lattice-Boltzmann simulations through improved initial conditions.
This study applies a multi-scale coarse-graining framework to building-resolving LES of urban morphologies to identify a morphology-dependent characteristic length scale, demonstrating that the accuracy of urban canopy parameterizations critically depends on the relationship between model resolution and this heterogeneity scale, thereby providing a systematic basis for developing scale-aware models for next-generation Numerical Weather Prediction.
This paper introduces a wind-relative reinforcement-learning framework for olfactory navigation in turbulent environments, demonstrating that an agent using only the time since the last odor detection and a locally estimated wind direction can outperform traditional strategies and adapt its behavior based on wind estimation quality in both mean wind and isotropic turbulence.
This paper presents a patient-specific Lattice Boltzmann method that models non-Newtonian blood flow in coiled intracranial aneurysms by treating the coil as an inhomogeneous porous medium, demonstrating the approach's validity for assessing post-treatment hemodynamics.
This paper presents a novel numerical framework combining Hermite spectral methods and second-order time integration to efficiently simulate turbulent dilute polymeric fluids with memory effects, revealing that such memory phenomena weaken the drag-reducing capabilities of polymer additives.
This paper introduces a kinetic closure for the filtered Boltzmann--BGK equation that models turbulent subfilter effects through a generalized collision operator without requiring scale separation or a Smagorinsky-type ansatz, demonstrating improved stability and reduced dissipation in numerical tests compared to classical approaches.
This study demonstrates through laboratory experiments and nonlinear simulations that the common assumption of summing individual wave components to calculate mean Lagrangian drift significantly underpredicts mass transport in focusing wave fields by up to 30%, revealing that local wave steepness drives these enhancements and necessitating a new theoretical framework based on the nonlinear Schrödinger equation.
This paper demonstrates that an online dynamic mode decomposition-based adaptive feedback control system effectively suppresses high-frequency resonant tones and shock trains in a supersonic dual-stream jet by stabilizing shear layer instabilities and mitigating intermittent low-pressure events, even under physical actuation constraints and varying sensor placements.