🔬 Category

physics.flu-dyn

1213 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.

Effects of gas diffusion layer thickness on PEM fuel cells with composite foam-rib flow fields

This study utilizes 3D multiphase non-isothermal simulations to demonstrate that while conventional rib flow fields require an optimal cathode GDL thickness, composite foam-rib flow fields achieve superior performance with thinner cathode GDLs driven by enhanced oxygen concentration, and that reducing anode GDL thickness in both designs lowers Ohmic polarization by increasing water content in the cathode ionomer.

Wei Gao, Qifeng Li, Kai Sun, Rui Chen, Zhizhao Che, Tianyou Wang2026-04-03🔬 physics.app-ph

Deep learning accelerated solutions of incompressible Navier-Stokes equations on non-uniform Cartesian grids

This paper introduces an enhanced HyDEA framework that utilizes Mesh-Conv operators and a novel multi-level distance vector map strategy to extend deep learning-accelerated solutions of the pressure Poisson equation to non-uniform Cartesian grids, enabling robust and generalizable simulations of incompressible flows around complex immersed boundaries.

Heming Bai, Dong Zhang, Shengze Cai, Xin Bian2026-04-03🔬 physics

Revisiting Conservativeness in Fluid Dynamics: Failure of Non-Conservative PINNs and a Path-Integral Remedy

This paper demonstrates that standard non-conservative Physics-Informed Neural Networks (PINNs) fail to capture correct shock speeds in unsteady fluid dynamics due to violations of Rankine–Hugoniot conditions, and proposes a path-integral framework based on DLM theory to successfully restore physical fidelity in primitive-variable formulations.

Arun Govind Neelan, Ferdin Sagai Don Bosco, Naveen Sagar Jarugumalli, Suresh Balaji Vedarethinam2026-04-03🔬 physics

Lattice Boltzmann framework for multiphase flows by Eulerian-Eulerian Navier-Stokes equations

This paper introduces a novel, dimension-independent Lattice Boltzmann framework that solves Eulerian-Eulerian multiphase flow equations with large density ratios and realistic drag coefficients without finite difference corrections, demonstrating excellent agreement with traditional solvers and promising efficient implementation on high-performance computing systems.

Matteo Maria Piredda, Pietro Asinari2026-04-02🔬 physics

VIVALDy: A Hybrid Generative Reduced-Order Model for Turbulent Flows, Applied to Vortex-Induced Vibrations

This paper introduces VIVALDy, a novel hybrid machine-learning framework combining a masked convolutional β\beta-VAE-GAN and a bidirectional transformer to accurately reconstruct turbulent flows and predict vortex-induced vibrations in moving cylinders using only minimal sensor inputs.

Niccolò Tonioni, Lionel Agostini, Franck Kerhervé, Laurent Cordier, Ricardo Vinuesa2026-04-02🔬 physics

Nonhomogeneous elastic turbulence in the two-dimensional Taylor-Couette flow

Through numerical simulations of the two-dimensional Taylor-Couette system, this study characterizes the onset of elastic turbulence and reveals that the resulting fully nonlinear dynamics are strongly nonhomogeneous and confined to an active region near the inner wall, where statistical properties align reasonably well with theoretical expectations despite spatial deviations.

Zhongxuan Hou, Stefano Berti, Teodor Burghelea, Francesco Romanò2026-04-02🔬 physics

Covariant Helmholtz-Hodge Decomposition: Resolving Spurious Vorticity via Acoustic Geometry

This paper introduces a covariant Helmholtz-Hodge decomposition based on an effective acoustic metric to resolve the ambiguity in separating acoustic and vortical fluctuations within thermodynamically inhomogeneous media, thereby eliminating the spurious vorticity leakage caused by thermal refraction and shock-induced bending that plagues traditional Euclidean methods.

Chanho Park, Yeachan Kwak, Seongim Choi2026-04-02🔬 physics

Covariant Chu-Kovasznay Decomposition: Resolving Thermodynamic Ambiguity in Compressible Flows

This paper introduces the Covariant Chu-Kovasznay Decomposition (CCKD), a geometric framework formulated on effective acoustic spacetime that resolves thermodynamic ambiguity in compressible flows by demonstrating that shock-turbulence interactions act as information-preserving, near-unitary scattering maps where entropy fluctuations are converted to sound via a geometric blue-shift mechanism.

Chanho Park, Gyeongho Gong, Yeachan Kwak, Seongim Choi2026-04-02🔬 physics