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Achievement of solutions in Navier-Stokes equation is one of challenging quests, especially for its closure problem. For achievement of particular solutions, there are variety of numerical simulations including Direct Numerical Simulation…

Computational Physics · Physics 2018-11-13 Jinu Lee , Sangseung Lee , Donghyun You

We carry out a direct numerical simulation (DNS) study that reveals the effects of polymers on statistically steady, forced, homogeneous, isotropic fluid turbulence. We find clear manifestations of dissipation-reduction phenomena: On the…

Fluid Dynamics · Physics 2011-02-01 Prasad Perlekar , Dhrubaditya Mitra , Rahul Pandit

Using clean numerical simulation (CNS) in which artificial numerical noise is negligible over a finite, sufficiently long interval of time, we provide evidence, for the first time, that artificial numerical noise in direct numerical…

Fluid Dynamics · Physics 2025-04-11 Shijun Liao , Shijie Qin

The large structures in the outer layer of turbulent wall flows are of great physical importance, because they contain a substantial fraction of the streamwise kinetic energy and of the Reynolds stresses. Nevertheless, the organization of…

Fluid Dynamics · Physics 2013-09-12 Juan C. del Alamo , Javier Jimenez

Many engineering and environmental surfaces exhibit spatial heterogeneity in the spanwise direction and encompass multiple surface length scales. When the dominant spanwise length scale is on the order of the largest flow scales (e.g., the…

Fluid Dynamics · Physics 2025-05-27 Mattias Nilsson-Takeuchi , Bharathram Ganapathisubramani

Fluid dynamics spans phenomena from the Cheerios effect to cosmic evolution and has been called the 'queen mother' of science. Traditional modelling relies on numerical methods, including finite differences, volumes, and elements, that…

Fluid Dynamics · Physics 2026-04-09 Kwame Agyei-Baah , Muhammad Rizwanur Rahman , E. R. Smith

Particle-resolved direct numerical simulation (PR-DNS) is performed for turbulent open channel flow over a smooth horizontal wall with a vertical cylinder and a dilute set of mobile, heavy, spherical particles. At the chosen parameter point…

Fluid Dynamics · Physics 2026-04-20 Leo Bürk , Artjom Hermann , Markus Weyrauch , Markus Uhlmann

We parameterize sub-grid scale (SGS) fluxes in sinusoidally forced two-dimensional turbulence on the $\beta$-plane at high Reynolds numbers (Re$\sim$25000) using simple 2-layer Convolutional Neural Networks (CNN) having only…

Fluid Dynamics · Physics 2023-04-12 Kaushik Srinivasan , Mickael D. Chekroun , James C. McWilliams

This paper introduces open-source computational fluid dynamics software named open computational fluid dynamic code for scientific computation with graphics processing unit (GPU) system (OpenCFD-SCU), developed by the authors for direct…

Fluid Dynamics · Physics 2022-12-21 Guanlin Dang , Shiwei Liu , Tongbiao Guo , Junyi Duan , Xinliang Li

A new hybrid RANS/LES technique, based on the hybrid filter proposed by Germano in 2004, has been studied. The novelty herein introduced is represented by the reconstruction of the Reynolds stress tensor. As a consequence, no explicit RANS…

Fluid Dynamics · Physics 2014-11-19 Antonella Abbà , Massimo Germano , Michele Nini , Marco Restelli

We present a data-driven framework for turbulence modeling, applied to flow prediction in the FDA nozzle. In this study, the standard RANS equations have been modified using an implicit-explicit hybrid approach. New variables were…

Fluid Dynamics · Physics 2025-10-02 Hossein Geshani , Mehrdad Raisee Dehkordi , Masoud Shariat Panahi

Traditional computational fluid dynamics calculates the physical information of the flow field by solving partial differential equations, which takes a long time to calculate and consumes a lot of computational resources. We build a fluid…

Fluid Dynamics · Physics 2022-02-28 Qiang Liu , Wei Zhu , Xiyu Jia , Feng Ma , Yu Gao

We present STREAmS, an in-house high-fidelity solver for large-scale, massively parallel direct numerical simulations (DNS) of compressible turbulent flows on graphical processing units (GPUs). STREAmS is written in the Fortran 90 language…

Computational Physics · Physics 2020-04-07 Matteo Bernardini , Davide Modesti , Francesco Salvadore , Sergio Pirozzoli

The precise simulation of turbulent flows is of immense importance in a variety of scientific and engineering fields, including climate science, freshwater science, and the development of energy-efficient manufacturing processes. Within the…

Fluid Dynamics · Physics 2024-06-10 Shengyu Chen , Peyman Givi , Can Zheng , Xiaowei Jia

Neural rendering can be used to reconstruct implicit representations of shapes without 3D supervision. However, current neural surface reconstruction methods have difficulty learning high-frequency geometry details, so the reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2022-09-23 Yiqun Wang , Ivan Skorokhodov , Peter Wonka

Hydrodynamics simulations are powerful tools for studying fluid behavior under physical forces, enabling extraction of features that reveal key flow characteristics. Traditional post-analysis methods offer high accuracy but incur…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-16 Kewei Yan , Yonghong Yan

We employ a resolvent-based methodology to estimate velocity and pressure fluctuations within turbulent channel flows at friction Reynolds numbers of approximately 180, 550 and 1000 using measurements of shear stress and pressure at the…

Fluid Dynamics · Physics 2021-10-04 Filipe R. Amaral , André V. G. Cavalieri , Eduardo Martini , Peter Jordan , Aaron Towne

Direct Numerical Simulations of two superposed fluids in a channel with a textured surface on the lower wall have been carried out. A parametric study varying the viscosity ratio between the two fluids has been performed to mimic both {\bf…

Fluid Dynamics · Physics 2019-05-22 I. Arenas , E. Garcia , M. K. Fu , P. Orlandi , M. Hultmark , S. Leonardi

Large-scale or high-resolution geologic models usually comprise a huge number of grid blocks, which can be computationally demanding and time-consuming to solve with numerical simulators. Therefore, it is advantageous to upscale geologic…

Machine Learning · Computer Science 2022-01-04 Nanzhe Wang , Qinzhuo Liao , Haibin Chang , Dongxiao Zhang

The efficient mixing of fluids is key in many applications, such as chemical reactions and nanoparticle precipitation. Detailed experimental measurements of the mixing dynamics are however difficult to obtain, and so predictive numerical…

Fluid Dynamics · Physics 2017-11-21 Tobias Schikarski , Wolfgang Peukert , Marc Avila