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We use a data-driven approach to model a three-dimensional turbulent flow using cutting-edge Deep Learning techniques. The deep learning framework incorporates physical constraints on the flow, such as preserving incompressibility and…

Fluid Dynamics · Physics 2021-12-08 Mohammadreza Momenifar , Enmao Diao , Vahid Tarokh , Andrew D. Bragg

With the development of high performance computer and experimental technology, the study of turbulence has accumulated a large number of high fidelity data. However, few general turbulence knowledge has been found from the data. So we use…

Fluid Dynamics · Physics 2024-06-17 ZhongXin Yang , XiangLin Shan , WeiWei Zhang

Turbulent fluid flows are among the most computationally demanding problems in science, requiring enormous computational resources that become prohibitive at high flow speeds. Physics-informed neural networks (PINNs) represent a radically…

Machine Learning · Computer Science 2025-10-14 Sifan Wang , Shyam Sankaran , Xiantao Fan , Panos Stinis , Paris Perdikaris

Turbulence constitutes an exceptionally complex and irregular flow phenomenon that manifests in liquids, gases, and plasma, making it ubiquitous in both natural processes and engineering applications. Given the relatively modest…

Fluid Dynamics · Physics 2025-07-08 Ziqi Ji , Penghao Duan , Gang Du

Turbulent states are ubiquitous in plasmas and the understanding of turbulence is fundamental in modern astrophysics. Numerical simulations, which are the state-of-the-art approach to the study of turbulence, require substantial computing…

Plasma Physics · Physics 2024-08-26 Daniela Maci , Rony Keppens , Fabio Bacchini

Turbulence remains one of the last unresolved problems of classical physics and a major bottleneck to accurate flow prediction in climate, aerospace, and energy systems. Industrial simulations therefore rely on averaged representations of…

Fluid Dynamics · Physics 2026-05-18 Zhuoran Liu , Haochen Wang , Zhuolin Zhao , Heng Xiao

When modelling turbulent flows, it is often the case that information on the forcing terms or the boundary conditions is either not available or overly complicated and expensive to implement. Instead, some flow features, such as the mean…

Prediction is a fundamental objective of science. It is more difficult for chaotic and complex systems like turbulence. Here we use information theory to quantify spatial prediction using experimental data from a turbulent soap film. At…

Fluid Dynamics · Physics 2014-12-05 Rory Cerbus , Walter Goldburg

High-resolution numerical simulations are utilized to examine isotropic turbulence in a compressible fluid when long wavelength velocity fluctuations approach light speed. Spectral analysis reveals an inertial sub-range of relativistic…

High Energy Astrophysical Phenomena · Physics 2013-01-04 Jonathan Zrake , Andrew MacFadyen

Relation of ultrametric analysis, wavelet theory and cascade models of turbulence is discussed. We construct the explicit solutions for the nonlinear ultrametric integral equation with quadratic nonlinearity. These solutions are built by…

Mathematical Physics · Physics 2011-05-10 S. V. Kozyrev

We describe a new method involving wavelet transforms for deriving the wind velocity associated with atmospheric turbulence layers from Generalized SCIDAR measurements. The algorithm analyses the cross-correlation of a series of…

Astrophysics · Physics 2016-08-30 B. Garcia-Lorenzo , J. J. Fuensalida

Using experimental transverse velocities data for very high Reynolds number turbulence, we suggest a model describing both formation of intermittency and asymmetry of turbulence. The model, called "bump-model" is a modification of…

Chaotic Dynamics · Physics 2015-06-26 S. I. Vainshtein

The random Fourier method (RFM) is widely employed for synthetic turbulence due to its mathematical clarity and simplicity. However, deviations remain between prescribed inputs and synthetic results, and the origin of these errors has not…

Fluid Dynamics · Physics 2025-10-16 Hongyuan Lin , Yi Liu , Shizhao Wang , Chun-Hian Lee

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…

Condensed Matter · Physics 2007-05-23 Y-h. Taguchi , Hideki Takayasu

Sampling synthetic turbulent fields as a computationally tractable surrogate for direct numerical simulations (DNS) is an important practical problem in various applications, and allows to test our physical understanding of the main…

Fluid Dynamics · Physics 2025-11-19 Timo Schorlepp , Katharina Kormann , Jeremiah Lübke , Tobias Schäfer , Rainer Grauer

An artificial neural-network-based subgrid-scale model using the resolved stress, which is capable of predicting untrained decaying isotropic turbulence, is developed. Providing the grid-scale strain-rate tensor alone as input leads the…

Fluid Dynamics · Physics 2023-05-17 Myeongseok Kang , Youngmin Jeon , Donghyun You

Turbulent flows have historically presented formidable challenges to predictive computational modeling. Traditional numerical simulations often require vast computational resources, making them infeasible for numerous engineering…

Fluid Dynamics · Physics 2023-11-15 Han Gao , Xu Han , Xiantao Fan , Luning Sun , Li-Ping Liu , Lian Duan , Jian-Xun Wang

Spatially developing round jet flows are fundamental to numerous engineering applications. This letter applies the wave-particle turbulence simulation (WPTS) method, a recently developed multiscale approach, to simulate a spatially…

Fluid Dynamics · Physics 2025-07-22 Xiaojian Yang , Kun Xu

We present a status report on a discrete approach to the the near-equilibrium statistical theory of three-dimensional turbulence, which generalizes earlier work by no longer requiring that the vorticity field be a union of discrete vortex…

Numerical Analysis · Mathematics 2025-10-20 G. I. Barenblatt , A. J. Chorin

This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…

Computational Physics · Physics 2025-03-11 Xiaojian Yang , Kun Xu