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 introduces an evidence-driven Bayesian formulation of Physics-Informed Neural Networks that utilizes a Laplace approximation to analytically compute model evidence, enabling efficient, sampling-free automatic optimization of loss weights and uncertainty quantification across various partial differential equations.
This paper presents a deep reinforcement learning framework that utilizes far-field acoustic measurements as the primary feedback signal to drive synthetic jet actuation, successfully suppressing unsteady wake dynamics behind a circular cylinder and achieving significant reductions in radiated noise and drag without relying on traditional velocity or pressure sensors.
This paper presents a mathematical analysis of a two-link flexible magnetic nano-swimmer under a rotating magnetic field, deriving explicit analytic solutions for its in-plane tumbling and spatial helical swimming regimes, conducting stability and bifurcation analysis, and optimizing its performance to advance biomedical applications.
This paper introduces a quantum-inspired tensor-network fractional-step method for simulating incompressible flows in curvilinear coordinates, demonstrating that highly compressed tensor representations of flow fields and operators achieve high accuracy with significant memory and runtime savings compared to standard finite difference simulations while remaining directly portable to quantum computers.
This paper presents a systematic quantum pathway for solving differential equations by combining block encoding with Quantum Singular Value Transformation (QSVT), demonstrating its application to heat and Burgers' equations while providing critical hardware resource estimates and scaling analyses that highlight current limitations and future directions for achieving quantum advantage.
This paper demonstrates that in driven Stokes flows, such as those in a Hele-Shaw cell, energy-optimal particle control paths correspond to geodesics of an emergent Riemannian metric, a geometric principle that governs both deterministic steering and anisotropic diffusion while generalizing to broader three-dimensional contexts.
This paper investigates the physical complexity of espresso brewing by demonstrating that the interplay between elasticity, porosity, and dissolution dynamics governs the non-linear pressure-flow relationship and solute concentration, supported by a minimal model validated through controlled experiments with a café-grade machine.
This study investigates the "butterfly effect" in Surface Quasi-Geostrophic turbulence, revealing that infinitesimal localized perturbations exhibit strong variability and undergo a prolonged transient energy decrease before growing, with the duration of this phase depending on the perturbation's initial location.
This paper proposes a self-supervised framework that reformulates steady computational fluid dynamics inference as a context-driven inpainting problem, enabling reusable flow priors that outperform traditional supervised models under boundary shifts and support local geometry editing.
This paper introduces a filtered Hilbert POD method to resolve mode mixing in turbulent bent-pipe flows, revealing that swirl-switching is an intrinsic instability of the curved section rather than a universal phenomenon, and demonstrating that downstream modes arise from distinct local shear layer mechanisms.