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Density varies spatiotemporally in low Mach number flows. Hence, incompressibility cannot be assumed, and the density must be accurately solved. Various methods have been proposed to analyze low Mach number flows, but their energy…

Fluid Dynamics · Physics 2025-02-13 Hideki Yanaoka , Yuji Sato

Complex fluids transition from laminar to transitory flow above a critical control parameter, akin to their Newtonian counterparts. In a continuum mechanics sense, fluid elements follow the ensuing complex trajectories, giving rise to…

We analyze data from direct numerical simulations of homogeneous and isotropic turbulence (at Re_\lambda \approx 280) and study the statistics of curvature and torsion of Lagrangian trajectories in order to extract informations on the…

Chaotic Dynamics · Physics 2009-09-11 Andrea Scagliarini

We propose an invariant feature space for the detection of viscous dominated and turbulent regions (i.e., boundary layers and wakes). The developed methodology uses the principal invariants of the strain and rotational rate tensors as input…

Fluid Dynamics · Physics 2023-02-22 Kheir-Eddine Otmani , Gerasimos Ntoukas , Esteban Ferrer

When simulating three-dimensional flows interacting with deformable and elastic obstacles, current methods often encounter complexities in the governing equations and challenges in numerical implementation. In this work, we introduce a…

Fluid Dynamics · Physics 2026-01-09 Andreu F. Gallen , Joan Muñoz Biosca , Mario Castro , Aurora Hernández-Machado

Blood flow reconstruction in the vasculature is important for many clinical applications. However, in clinical settings, the available data are often quite limited. For instance, Transcranial Doppler ultrasound (TCD) is a noninvasive…

Image and Video Processing · Electrical Eng. & Systems 2024-03-18 Shaghayegh Z. Ashtiani , Mohammad Sarabian , Kaveh Laksari , Hessam Babaee

The field of novel-view synthesis has recently witnessed the emergence of 3D Gaussian Splatting, which represents scenes in a point-based manner and renders through rasterization. This methodology, in contrast to Radiance Fields that rely…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Fengyi Zhang , Yadan Luo , Tianjun Zhang , Lin Zhang , Zi Huang

Let ${\mathfrak{G}}\subset\mathbb{R}^{3}$ with $vol(\mathfrak{G})\sim L^{3}$. Let ${\mathscr{T}}(x)$ be a Gaussian random field $\forall~x\in\mathfrak{G}$ with expectation $\mathbf{E}[{\mathscr{T}}(x)]=0$ and correlation…

Probability · Mathematics 2024-09-18 Steven D Miller

The immersed boundary (IB) method is a general mathematical framework for studying problems involving fluid-structure interactions in which an elastic structure is immersed in a viscous incompressible fluid. In the IB formulation, the fluid…

Numerical Analysis · Mathematics 2020-10-01 Yuanxun Bao , Alexander D. Kaiser , Jason Kaye , Charles S. Peskin

We study a one-dimensional model for heavy particles in a compressible fluid. The fluid-velocity field is modelled by a persistent Gaussian random function, and the particles are assumed to be weakly inertial. Since one-dimensional…

Fluid Dynamics · Physics 2019-08-06 J. Meibohm , B. Mehlig

We introduce a continuous Galerkin finite element discretization of the non-hydrostatic Boussinesq approximation of the Navier-Stokes equations, suitable for various applications such as coastal ocean dynamics and ice-ocean interactions,…

Numerical Analysis · Mathematics 2024-12-16 Lukas Lundgren , Christian Helanow , Jonathan Wiskandt , Inga Monika Koszalka , Josefin Ahlkrona

The 3D Gaussian splatting method has drawn a lot of attention, thanks to its high performance in training and high quality of the rendered image. However, it uses anisotropic Gaussian kernels to represent the scene. Although such…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Yuanhao Gong , Lantao Yu , Guanghui Yue

The interaction of two isotropic turbulent fields of equal integral scale but different kinetic energy generates the simplest kind of inhomogeneous turbulent field. In this paper we present a numerical experiment where two time decaying…

Fluid Dynamics · Physics 2012-11-29 Daniela Tordella , Michele Iovieno , Peter Roger Bailey

In our previous work~\cite{SanchisAgudoVinuesa2025PRL}, we argued that viscous dissipation in turbulence can be understood as the macroscopic imprint of microscopic path uncertainty, and showed that a kernel variance field $s(y)$…

Fluid Dynamics · Physics 2026-01-08 Marcial Sanchis-Agudo , Ricardo Vinuesa

Embodied 3D Semantic Scene Completion (SSC) infers dense geometry and semantics from continuous egocentric observations. Most existing Gaussian-based methods rely on random initialization of many primitives within predefined spatial bounds,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Rui Qian , Haozhi Cao , Tianchen Deng , Tianxin Hu , Weixiang Guo , Shenghai Yuan , Lihua Xie

This paper is an attempt to introduce methods and concepts of the Riemann-Cartan geometry largely used in such physical theories as general relativity, gauge theories, solid dynamics, etc. to fluid dynamics in general and to studying and…

Fluid Dynamics · Physics 2019-05-01 Ilya Peshkov , Evgeniy Romenski , Michael Dumbser

Stable and accurate finite element methods are presented for Darcy flow in heterogeneous porous media with an interface of discontinuity of the hydraulic conductivity tensor. Accurate velocity fields are computed through global or local…

Numerical Analysis · Mathematics 2025-05-26 Maicon R. Correa , Abimael F. D. Loula

We study the Lagrangian trajectories of statistically isotropic, homogeneous, and stationary divergence free spatiotemporal random vector fields. We design this advecting Eulerian velocity field such that it gets asymptotically rough and…

Fluid Dynamics · Physics 2020-07-08 Jason Reneuve , Laurent Chevillard

This work is concerned with a simple model for a polar fluid, a Gaussian field model based on the excess density and on the polarization. It is a convenient framework to implement the dielectric properties of correlated liquids that stem…

Chemical Physics · Physics 2018-04-04 Hélène Berthoumieux

Learning PDE dynamics for fluids increasingly relies on neural operators and Transformer-based models, yet these approaches often lack interpretability and struggle with localized, high-frequency structures while incurring quadratic cost in…

Machine Learning · Computer Science 2026-02-26 Zhihao Li , Yu Feng , Zhilu Lai , Wei Wang