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SAM, a plant-level system analysis tool for advanced reactors (SFR, LFR, MSR/FHR) is under development at Argonne. As a modern system code, SAM aims to improve the predictions of 3D flows relevant to reactor safety during transient…

Fluid Dynamics · Physics 2020-05-04 Yangmo Zhu , Nam Dinh , Rui Hu , Adam Kraus

Ocean models at intermediate resolution (1/4 degree), which partially resolve mesoscale eddies, can be seen as Large eddy simulations (LES) of the primitive equations, in which the effect of unresolved eddies must be parameterized. In this…

Atmospheric and Oceanic Physics · Physics 2023-10-06 Pavel Perezhogin , Andrey Glazunov

In Part I of this study, we analyzed the motion of inertial particles in isotropic turbulence in the absence of gravity using direct numerical simulation (DNS). Here, in Part II, we introduce gravity and study its effect over a wide range…

Fluid Dynamics · Physics 2016-05-25 Peter J. Ireland , Andrew D. Bragg , Lance R. Collins

The inclusion of convection in stellar evolution models lacks realism, especially near convective-radiative interfaces. Furthermore, the interaction of convection with oscillations prevent us from accurately predicting seismic frequencies,…

Solar and Stellar Astrophysics · Physics 2025-10-31 J. Philidet , K. Belkacem

Our work is motivated by the analysis of ash plume dynamics, arising in the study of volcanic eruptions. Such phenomena are characterized by large Reynolds number (exceeding $10^7$) and a large number of polydispersed particles~[1]. Thus,…

Smoothed Particle Hydrodynamics (SPH) is a Lagrangian method for solving the fluid equations that is commonplace in astrophysics, prized for its natural adaptivity and stability. The choice of variable to smooth in SPH has been the topic of…

Astrophysics of Galaxies · Physics 2021-05-26 Josh Borrow , Matthieu Schaller , Richard G. Bower

In the Large Eddy Simulation (LES) framework for modeling a turbulent flow, when the large scale velocity field is defined by low-pass filtering the full velocity field, a Taylor series expansion of the full velocity field in terms of the…

Fluid Dynamics · Physics 2012-10-09 Balasubramanya T. Nadiga , Freddy Bouchet

Recent advances in data-driven turbulence modeling have established tensor basis neural networks (TBNN) as a physically grounded framework for Reynolds-stress closure in Reynolds-averaged Navier-Stokes (RANS) simulations. However, their…

Fluid Dynamics · Physics 2026-04-13 Zelong Yuan , Yuzhu Pearl Li

We present a phenomenological model for granular suspension rheology in which particle interactions enter as constraints to relative particle motion. By considering constraints that are formed and released by stress respectively, we derive…

Soft Condensed Matter · Physics 2018-09-26 B. M. Guy , J. A. Richards , D. J. M. Hodgson , E. Blanco , W. C. K. Poon

The problem of accretion of small particles by a sphere embedded in a mean flow is studied in the case where the particles undergo inelastic collisions with the solid object. The collision efficiency, which gives the flux of particles…

Fluid Dynamics · Physics 2018-02-21 Robin Vallée , Christophe Henry , Elie Hachem , Jérémie Bec

Statistical properties of turbulent Rayleigh-Benard convection at low Prandtl numbers (Pr), which are typical for liquid metals such as mercury, gallium or liquid sodium, are investigated in high-resolution three-dimensional spectral…

Fluid Dynamics · Physics 2016-09-13 Janet D. Scheel , Joerg Schumacher

We consider suspensions of neutrally-buoyant finite-size rigid spherical particles in channel flow and investigate the relation between the particle dynamics and the mean bulk behavior of the mixture for Reynolds numbers $500 \le Re \le…

Fluid Dynamics · Physics 2015-04-21 Iman Lashgari , Francesco Picano , Wim Paul Breugem , Luca Brandt

This paper presents a Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) method for solving the two-equation Reynolds-Averaged Navier-Stokes (RANS) model. The turbulent wall-bounded flow with or without mild flow separation, a…

Fluid Dynamics · Physics 2025-01-31 Feng Wang , Zhongguo Sun , Xiangyu Hu

Geophysical fluid flows are predominantly turbulent and often strongly affected by the Earth's rotation, as well as by stable density stratification. Using direct numerical simulations of forced Boussinesq equations, we study the influence…

Normal stresses in sheared suspensions of non-Brownian particles are obtained from numerical simulations in the viscous regime. The stresses are determined in homogeneous shear of non-buoyant particles and by analyzing shear-induced…

Soft Condensed Matter · Physics 2024-10-02 William Chèvremont , Bruno Chareyre , Hugues Bodiguel

Turbulence models attempt to account for unresolved dynamics and diffusion in hydrodynamical simulations. We develop a common framework for two-equation Reynolds-Averaged Navier-Stokes (RANS) turbulence models, and we implement six models…

Astrophysics of Galaxies · Physics 2017-03-28 Matthew D. Goodson , Fabian Heitsch , Karl Eklund , Virginia A. Williams

Numerical models based on Reynolds-Averaged Navier-Stokes (RANS) equations are widely used in engineering turbulence modeling. However, the RANS predictions have large model-form uncertainties for many complex flows. Quantification of these…

Computational Physics · Physics 2017-01-25 Jian-Xun Wang , Rui Sun , Heng Xiao

We use silicon strip detectors (originally developed for the CLEO III high energy particle physics experiment) to measure fluid particle trajectories in turbulence with temporal resolution of up to 70,000 frames per second. This high frame…

Fluid Dynamics · Physics 2009-11-07 Greg A. Voth , A. La Porta , Alice M. Crawford , Eberhard Bodenschatz , Jim Alexander

The ultimate goal of a sound theory of turbulence in fluids is to close in a rational way the Reynolds equations, namely to express the tensor of turbulent stress as a function of the time average of the velocity field. Based on the idea…

Fluid Dynamics · Physics 2021-07-14 Yves Pomeau , Martine Le Berre

Penalized regression methods, such as $L_1$ regularization, are routinely used in high-dimensional applications, and there is a rich literature on optimality properties under sparsity assumptions. In the Bayesian paradigm, sparsity is…

Statistics Theory · Mathematics 2012-12-27 Anirban Bhattacharya , Debdeep Pati , Natesh S. Pillai , David B. Dunson
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