English
Related papers

Related papers: Small scale reconstruction in three-dimensional Ko…

200 papers

This paper presents reconstructions of homogeneous targets from the 2D and 3D Fresnel databases by one-step imaging methods based on the computation of topological derivative and topological energy fields. The electromagnetic inverse…

Analysis of PDEs · Mathematics 2025-01-28 A. Carpio , M. Pena , M. L. Rapún

Fabrication process variations are a major source of yield degradation in the nano-scale design of integrated circuits (IC), microelectromechanical systems (MEMS) and photonic circuits. Stochastic spectral methods are a promising technique…

Computational Engineering, Finance, and Science · Computer Science 2016-11-08 Zheng Zhang , Tsui-Wei Weng , Luca Daniel

We study the sub-grid scale characteristics of a vorticity-transport-based approach for large-eddy simulations. In particular, we consider a multi-dimensional upwind scheme for the vorticity transport equations and establish its properties…

Fluid Dynamics · Physics 2021-02-05 Daniel Foti , Karthik Duraisamy

From a simple path integral involving a variable volatility in the velocity differences, we obtain velocity probability density functions with exponential tails, resembling those observed in fully developed turbulence. The model yields…

chao-dyn · Physics 2009-10-28 B. Holdom

We test a subgrid-scale spectral model of rotating turbulent flows against direct numerical simulations. The particular case of Taylor-Green forcing at large scale is considered, a configuration that mimics the flow between two counter…

Fluid Dynamics · Physics 2008-12-11 J. Baerenzung , P. D. Mininni , A. Pouquet , H. Politano , Y. Ponty

This paper applies variational data assimilation to inundation problems governed by the shallow water equations with wetting and drying. The objective of the assimilation is to recover an unknown time-varying wave profile at an open ocean…

Fluid Dynamics · Physics 2017-06-07 S. W Funke , P. E Farrell , M. D. Piggott

Analyzing large-scale data from simulations of turbulent flows is memory intensive, requiring significant resources. This major challenge highlights the need for data compression techniques. In this study, we apply a physics-informed Deep…

Fluid Dynamics · Physics 2022-07-26 Mohammadreza Momenifar , Enmao Diao , Vahid Tarokh , Andrew D. Bragg

A turbulent flow is characterized by velocity fluctuations excited in an extremely broad interval of wave numbers $k> \Lambda_{f}$ where $\Lambda_{f}$ is a relatively small set of the wave-vectors where energy is pumped into fluid by…

Fluid Dynamics · Physics 2015-06-22 Victor Yakhot

In many data science applications, the objective is to extract appropriately-ordered smooth low-dimensional data patterns from high-dimensional data sets. This is challenging since common sorting algorithms are primarily aiming at finding…

Machine Learning · Computer Science 2024-10-30 Illia Horenko , Lukas Pospisil

The high-order statistics of fluctuations in velocity gradients in the crossover range from the inertial to the Kolmogorov and sub-Kolmogorov scales are studied by direct numerical simulations (DNS) of homogeneous isotropic turbulence with…

Chaotic Dynamics · Physics 2011-02-11 Joerg Schumacher , Katepalli R. Sreenivasan , Victor Yakhot

The three-dimensional reconstruction of vocal folds in medicine usually involves endoscopy and an approach to extract depth information like structured light or stereo matching of images. The resulting mesh can accurately represent the…

Fluid Dynamics · Physics 2023-10-06 Daniel Zieger , Christoph Näger , Stefan Becker , Tobias Günther

The current understanding of MHD turbulence envisions turbulent eddies which are anisotropic in all three directions. In the plane perpendicular to the local mean magnetic field, this implies that such eddies become current-sheet-like…

Plasma Physics · Physics 2017-06-21 N. F. Loureiro , S. Boldyrev

A data-driven algorithm is proposed that employs sparse data from velocity and/or scalar sensors to forecast the future evolution of three dimensional turbulent flows. The algorithm combines time-delayed embedding together with Koopman…

Fluid Dynamics · Physics 2026-03-04 George Papadakis , Shengqi Lu

Markov random fields are used to model high dimensional distributions in a number of applied areas. Much recent interest has been devoted to the reconstruction of the dependency structure from independent samples from the Markov random…

Computational Complexity · Computer Science 2010-03-09 Guy Bresler , Elchanan Mossel , Allan Sly

We introduce a time-dimensional reduction method for the inverse source problem in linear elasticity, where the goal is to reconstruct the initial displacement and velocity fields from partial boundary measurements of elastic wave…

Numerical Analysis · Mathematics 2025-06-17 Trong D. Dang , Chanh V. Le , Khoa D. Luu , Loc H Nguyen

Recent developments in turbulence are focused on the effect of large scale anisotropy on the small scale statistics of velocity increments. According to Kolmogorov, isotropy is recovered in the large Reynolds number limit as the scale is…

Chaotic Dynamics · Physics 2009-11-11 C. M. Casciola , P. Gualtieri , B. Jacob , R. Piva

Redshift space distortions (RSD) in the void-galaxy correlation $\xi^s$ provide information on the linear growth rate of structure in low density environments. Accurate modelling of these RSD effects can also allow the use of voids in…

Cosmology and Nongalactic Astrophysics · Physics 2018-10-17 Seshadri Nadathur , Paul Carter , Will Percival

We present the results of a search of log-periodic corrections to scaling in the moments of the energy dissipation rate in experiments at high Reynolds number (2500) of three-dimensional fully developed turbulence. A simple dynamical…

Statistical Mechanics · Physics 2009-11-07 Wei-Xing Zhou , Didier Sornette

Numerical and physical experiments on two-dimensional (2d) turbulence show that the differences of transverse components of velocity field are well described by a gaussian statistics and Kolmogorov scaling exponents. In this case the…

Chaotic Dynamics · Physics 2009-10-31 Victor Yakhot

We analyze the data stemming from a forced incompressible hydrodynamic simulation on a grid of 2048^3 regularly spaced points, with a Taylor Reynolds number of Re~1300. The forcing is given by the Taylor-Green flow, which shares…

Fluid Dynamics · Physics 2009-11-13 P. D. Mininni , A. Alexakis , A. Pouquet