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 paper investigates how departures from the ideal buoyancy balance in natural doubly diffusive convection affect the formation and stability of localized patterns, such as convectons and anticonvectons, by examining how the absence of a steady conduction state unfolds their bifurcation processes.
This paper introduces a novel, fully differentiable simulation framework that unifies computational fluid dynamics and machine learning, enabling end-to-end optimization and data-driven modeling for multi-scale flows across both continuum and rarefied regimes.
This paper presents the first analytical and numerical solutions to the three-phase Stefan problem that account for simultaneous melting, solidification, boiling, and condensation by incorporating critical jump conditions such as density changes and kinetic energy.
This study demonstrates through 3D numerical simulations that accounting for micromagnetorotation (MMR) is essential in modeling stenosed blood flow, as it significantly alters velocity, vorticity, and wall shear stress compared to traditional MHD micropolar models that ignore this magnetic torque effect.
This paper presents a novel volume penalization technique that uses a perturbation approach to efficiently and accurately simulate acoustically-actuated flows in complex microchannels by segregating the problem into harmonic first-order and time-averaged second-order systems.
This paper demonstrates that in rotating 3D turbulence, near-resonant interactions between 3D inertial waves and large-scale 2D flows create an emergent conservation law that drives energy into 2D structures, though increasing rotation eventually suppresses this transfer and triggers a transition back to 3D-dominated turbulence.
The paper proposes a three-tier machine learning framework that uses Diffusion Maps to extract latent representations, SINDy or MVAR to learn reduced-order models, and k-NN-based interpolation for reconstruction, enabling the accurate and mass-preserving prediction of complex, mass-constrained spatio-temporal dynamics without explicitly identifying the underlying partial differential equations.
This study numerically demonstrates how controlling the evaporation regime (reaction-limited vs. diffusion-limited) and filament properties (length, stiffness, and concentration) can manipulate deposition patterns and alignment to optimize the morphology and electrical conductivity of printed conductive networks.
This study compares the widely used Borgnakke-Larsen model with the more theoretically rigorous Pullin model for simulating translational-rotational energy exchange in diatomic gases using the DSMC method, demonstrating that the Pullin model provides a more consistent physical foundation while maintaining comparable efficiency to the BL model in highly rarefied flows.
This paper investigates the scattering and frequency conversion of acoustic waves interacting with single and double spatio-temporal interfaces, analyzing how different velocity regimes (subsonic, intersonic, and supersonic) affect wave behavior through analytical derivations and numerical simulations.