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This research presents a new turbulence generation method based on stochastic wavelets and tests its various properties in both homogeneous and inhomogeneous turbulence. Turbulence field can be generated with less basis compared to previous…

数值分析 · 数学 2018-11-14 Yifan Du , Guang Lin

A simple variant of recycling and rescaling method to generate inflow turbulence using unstructured grid CFD codes is presented. The method has been validated on large eddy simulation of spatially developing flat plate turbulent boundary…

流体动力学 · 物理学 2014-08-22 Sunil K. Arolla

Ground based long-range passive imaging systems often suffer from degraded image quality due to a turbulent atmosphere. While methods exist for removing such turbulent distortions, many are limited to static sequences which cannot be…

图像与视频处理 · 电气工程与系统科学 2020-09-02 Zhiyuan Mao , Nicholas Chimitt , Stanley Chan

Synthetic turbulence models are a useful tool that provide realistic representations of turbulence, necessary to test theoretical results, to serve as background fields in some numerical simulations, and to test analysis tools. Models of 1D…

流体动力学 · 物理学 2016-11-15 Francesco Malara , Francesca Di Mare , Giuseppina Nigro , Luca Sorriso-Valvo

Simulating atmospheric turbulence is an essential task for evaluating turbulence mitigation algorithms and training learning-based methods. Advanced numerical simulators for atmospheric turbulence are available, but they require evaluating…

光学 · 物理学 2020-06-24 Nicholas Chimitt , Stanley H. Chan

Turbulence is a complex system exhibiting both universal statistical features and prominent coherent structures. We model turbulence using coherent vortices distributed within a multi-scale statistical framework, termed `woven turbulence'.…

流体动力学 · 物理学 2025-12-04 Zishuo Han , Weiyu Shen , Yue Yang

State-of-the-art atmospheric turbulence image restoration methods utilize standard image processing tools such as optical flow, lucky region and blind deconvolution to restore the images. While promising results have been reported over the…

图像与视频处理 · 电气工程与系统科学 2019-05-21 Nicholas Chimitt , Zhiyuan Mao , Guanzhe Hong , Stanley H. Chan

The present work proposes an inflow turbulence generation strategy using deep learning methods. This is achieved with the help of an autoencoder architecture with two different types of operational layers in the latent-space: a fully…

流体动力学 · 物理学 2019-10-16 Aakash Vijay Patil

Simulations of elastic turbulence, the chaotic flow of highly elastic and inertialess polymer solutions, are plagued by numerical difficulties: The chaotically advected polymer conformation tensor develops extremely large gradients and can…

流体动力学 · 物理学 2024-11-27 Sumithra R. Yerasi , Jason R. Picardo , Anupam Gupta , Dario Vincenzi

In this paper we present a method for matrix inversion based on Cholesky decomposition with reduced number of operations by avoiding computation of intermediate results; further, we use fixed point simulations to compare the numerical…

数学软件 · 计算机科学 2013-10-21 Aravindh Krishnamoorthy , Deepak Menon

Wave turbulence is the study of the long-time statistical behaviour of equations describing a set of weakly non-linear interacting waves. Such a theory, which has a natural asymptotic closure, allows us to probe the nature of turbulence…

流体动力学 · 物理学 2023-10-24 Sebastien Galtier

Fully developed turbulence is analised with the lattice model employing vortex tube representation which is introduced recently by the authors. Several characteric features observed in experiments and direct numeric integrations are…

凝聚态物理 · 物理学 2007-05-23 Y-h. Taguchi , Hideki Takayasu

FEARLESS (Fluid mEchanics with Adaptively Refined Large Eddy SimulationS) is a numerical scheme for modelling subgrid-scale turbulence in cosmological adaptive mesh refinement simulations. In this contribution, the main features of this…

宇宙学与河外天体物理 · 物理学 2012-10-18 L. Iapichino , W. Schmidt , J. C. Niemeyer , J. Merklein

Plasma turbulence simulations are often computationally expensive with delicate numerical stability. Yet, long simulations are needed to generate uncorrelated turbulence data for studies such as microwave scattering through density…

等离子体物理 · 物理学 2017-11-17 Jarrod Leddy , Chris Bowman , Kieran Gibson , Ben Dudson

When a planar shock wave interacts with a random pattern of pre-shock density non-uniformities, it generates an anisotropic turbulent velocity/vorticity field. This turbulence plays an important role at the early stages of the mixing…

流体动力学 · 物理学 2015-05-19 Cesar Huete Ruiz de Lira

Approximate deconvolution forms a mathematical framework for the structural modeling of turbulence. The sub-filter scale flow quantities are typically recovered by using the Van Cittert iterative procedure. In this paper, however, we put…

流体动力学 · 物理学 2017-07-31 Omer San , Prakash Vedula

A modified method is presented to generate artificial magnetic turbulence that is used for test-particle simulations. Such turbulent fields are obtained from the superposition of a set of wave modes with random polarizations and random…

高能天体物理现象 · 物理学 2013-06-17 R. C. Tautz , A. Dosch

We present a new method for the generation of atmospheric turbulence phase screens based on the frequency shift property of the Fourier transform. This method produces low spatial frequency distortions without additional computation time…

光学 · 物理学 2020-01-08 Daniel A. Paulson , Chensheng Wu , Christopher C. Davis

A novel random field model or the reconstruction of turbulent velocity fluctuations from inhomogeneous characteristic flow quantities in terms of stochastic Fourier-type integrals has recently been introduced and analyzed by the authors.…

流体动力学 · 物理学 2026-04-30 Markus Antoni , Quinten Kürpick , Felix Lindner , Nicole Marheineke , Raimund Wegener

Magnetic reconnection is a process that changes magnetic field topology in highly conducting fluids. Within the standard Sweet-Parker model, this process would be too slow to explain observations (e.g. solar flares). In reality, the process…

星系天体物理 · 物理学 2017-04-05 Grzegorz Kowal , Diego A. Falceta-Gonçalves , Alex Lazarian , Ethan T. Vishniac
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