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The problem of classifying turbulent environments from partial observation is key for some theoretical and applied fields, from engineering to earth observation and astrophysics, e.g. to precondition searching of optimal control policies in…

Fluid Dynamics · Physics 2022-10-19 Michele Buzzicotti , Fabio Bonaccorso

Purpose: Computational Fluid Dynamics (CFD) simulations are performed to investigate the impact of adding a grid to a two-inlet dry powder inhaler (DPI). The purpose of the paper is to show the importance of the correct choice of closure…

Computational Engineering, Finance, and Science · Computer Science 2021-01-27 David F Fletcher , Vishal Chaugule , Larissa Gomes dos Reis , Paul M Young , Daniela Traini , Julio Soria

A new methodology based on energy flux similarity is suggested in this paper for large eddy simulation (LES) of transitional and turbulent flows. Existing knowledge reveals that the energy cascade generally exists in transitional and…

Fluid Dynamics · Physics 2019-10-31 Han Qi , Xinliang Li , Hao Zhou , Changping Yu

In this paper, a turbulence model based on deep neural network is developed for turbulent flow around airfoil at high Reynolds numbers. According to the data got from the Spalart-Allmaras (SA) turbulence model, we build a neural network…

Fluid Dynamics · Physics 2021-11-29 Xuxiang Sun , Wenbo Cao , Yilang Liu , Linyang Zhu , Weiwei Zhang

Recent learning-based methods for event-based optical flow estimation utilize cost volumes for pixel matching but suffer from redundant computations and limited scalability to higher resolutions for flow refinement. In this work, we take…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Daikun Liu , Lei Cheng , Teng Wang , changyin Sun

In this study we investigate shallow turbidity density currents and underflows from mechanical point of view. We propose a simple hyperbolic model for such flows. On one hand, our model is based on very basic conservation principles. On the…

Fluid Dynamics · Physics 2020-02-20 Valery Liapidevskii , Denys Dutykh , Marguerite Gisclon

Experimental science is increasingly driven by instruments that produce vast volumes of data and thus a need to manage, compute, describe, and index this data. High performance and distributed computing provide the means of addressing the…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-03-12 Jim Pruyne , Valerie Hayot-Sasson , Weijian Zheng , Ryan Chard , Justin M. Wozniak , Tekin Bicer , Kyle Chard , Ian T. Foster

The numerical modeling of hydraulic jumps remains challenging due to complex interactions among free-surface deformation, air entrainment and detrainment, and turbulent bubble transport. Whereas accurate prediction of these flows is…

Fluid Dynamics · Physics 2026-05-08 L. D'Angelo , F. Zabaleta , G. E. Spadari , P. Consol-Lizzi , F. A. Bombardelli

This application paper presents a comprehensive experimental evaluation of the suitability of Topological Data Analysis (TDA) for the quantitative comparison of turbulent flows. Specifically, our study documents the usage of the persistence…

We propose two-equations models in order to capture the dynamics of a turbulent plasma undergoing compression and experiencing large viscosity variations. The models account for possible relaminarization phases and rapid viscosity changes…

In this paper we propose a new modeling framework for large eddy simulations (LES) of particle-laden turbulent flows that captures the interaction between the particle and fluid phase on both the resolved and subgrid-scales. Unlike the vast…

Fluid Dynamics · Physics 2023-10-26 Max Hausmann , Fabien Evrard , Berend van Wachem

Fluid flow is a widely applied physical problem, crucial in various fields. Due to the highly nonlinear and chaotic nature of fluids, analyzing fluid-related problems is exceptionally challenging. Computational fluid dynamics (CFD) is the…

Computational Engineering, Finance, and Science · Computer Science 2025-02-06 Fan Lei

This paper presents a novel generative model to synthesize fluid simulations from a set of reduced parameters. A convolutional neural network is trained on a collection of discrete, parameterizable fluid simulation velocity fields. Due to…

Machine Learning · Computer Science 2019-09-05 Byungsoo Kim , Vinicius C. Azevedo , Nils Thuerey , Theodore Kim , Markus Gross , Barbara Solenthaler

Modelling sediment transport in environmental turbulent fluids is a challenge. This article develops a sound model of the lateral transport of suspended sediment in environmental fluid flows such as floods and tsunamis. The model is…

Dynamical Systems · Mathematics 2014-07-08 Meng Cao , A. J. Roberts

For turbulent bubbly flows, multi-phase simulations resolving both the liquid and bubbles are prohibitively expensive in the context of different natural phenomena. One example is breaking waves, where bubbles strongly influence wave impact…

Cornerstone of this research is the examination of fluid flow around NACA0012 airfoil, with the aim of the numerical validation between the experimental results in the wind tunnel and the Lattice Boltzmann Method (LBM) analysis, for the…

Fluid Dynamics · Physics 2023-02-13 Andro Rak , Luka Grbčić , Ante Sikirica , Lado Kranjčević

A computational fluid dynamics (CFD) simulation framework for fluid-flow prediction is developed on the Tensor Processing Unit (TPU) platform. The TPU architecture is featured with accelerated dense matrix multiplication, large high…

Computational Physics · Physics 2022-03-02 Qing Wang , Matthias Ihme , Yi-Fan Chen , John Anderson

In this work we present a reduced basis Smagorinsky turbulence model for steady flows. We approximate the non-linear eddy diffusion term using the Empirical Interpolation Method, and the velocity-pressure unknowns by an independent…

The need for accurate and fast scale-resolving simulations of fluid flows, where turbulent dispersion is a crucial physical feature, is evident. Large-eddy simulations (LES) are computationally more affordable than direct numerical…

Fluid Dynamics · Physics 2025-12-30 Justin Plogmann , Oliver Brenner , Patrick Jenny

State estimation from limited sensor measurements is ubiquitously found as a common challenge in a broad range of fields including mechanics, astronomy, and geophysics. Fluid mechanics is no exception -- state estimation of fluid flows is…

Fluid Dynamics · Physics 2022-06-01 Taichi Nakamura , Koji Fukagata
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