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Mechanisms of nonhelical large-scale dynamos (shear-current dynamo and effect of homogeneous kinetic helicity fluctuations with zero mean) in a homogeneous turbulence with large-scale shear are discussed. We have found that the…

Astrophysics · Physics 2009-11-13 I. Rogachevskii , N. Kleeorin

In this work, we propose a novel phase-field model for the simulation of two-phase flows that is accurate, conservative, bounded, and robust. The proposed model conserves the mass of each of the phases, and results in bounded transport of…

Computational Physics · Physics 2022-08-23 Suhas S. Jain

Hydromagnetic turbulence affects the evolution of large-scale magnetic fields through mean-field effects like turbulent diffusion and the $\alpha$ effect. For stronger fields, these effects are usually suppressed or quenched, and additional…

Solar and Stellar Astrophysics · Physics 2014-10-13 Bidya Binay Karak , Matthias Rheinhardt , Axel Brandenburg , Petri J. Kapyla , Maarit J. Kapyla

The field of scientific machine learning and its applications to numerical analyses such as CFD has recently experienced a surge in interest. While its viability has been demonstrated in different domains, it has not yet reached a level of…

Fluid Dynamics · Physics 2025-03-19 Giuseppe Bruni , Sepehr Maleki , Senthil K Krishnababu

We present a novel asymptotic-preserving semi-implicit finite element method for weakly compressible and incompressible flows based on compatible finite element spaces. The momentum is sought in an $H(\mathrm{div})$-conforming space,…

Numerical Analysis · Mathematics 2024-07-16 Enrico Zampa , Michael Dumbser

The first estimation of the energy cascade rate ${|\epsilon_C|}$ of magnetosheath turbulence is obtained using the CLUSTER and THEMIS spacecraft data and an exact law of compressible isothermal magnetohydrodynamics turbulence.…

Space Physics · Physics 2018-02-07 Lina Hadid , Fouad Sahraoui , Sebastien Galtier , Shiyong Huang

A new simulation set-up is proposed for studying mean field dynamo action. The model combines the computational advantages of local cartesian geometry with the ability to include a shear profile that resembles the sun's differential…

Astrophysics · Physics 2007-05-23 Axel Brandenburg , Christer Sandin

Three-dimensional numerical simulations of decaying turbulence in a magnetized plasma are performed using a so-called FLR-Landau fluid model which incorporates linear Landau damping and finite Larmor radius (FLR) corrections. It is shown…

Plasma Physics · Physics 2015-05-30 P. Hunana , D. Laveder , T. Passot , P. L. Sulem , D. Borgogno

Certain aspects of the mean-field theory of turbulent passive scalar transport and of mean-field electrodynamics are considered with particular emphasis on aspects of compressible fluids. It is demonstrated that the total mean-field…

Astrophysics of Galaxies · Physics 2015-03-19 Karl-Heinz Rädler , Axel Brandenburg , Fabio Del Sordo , Matthias Rheinhardt

We present a comprehensive study of the effective Conformal Field Theory (CFT) describing the low energy excitations of a gas of spinless interacting fermions on a circle in the gapless regime (Luttinger liquid). Functional techniques and…

Mesoscale and Nanoscale Physics · Physics 2009-10-30 P. Degiovanni , Ch. Chaubet , R. Melin

This paper studies the nonlinear evolution of magnetic field turbulence in proximity of steady ideal MHD configurations characterized by a small electric current, a small plasma flow, and approximate flux surfaces, a physical setting that…

Plasma Physics · Physics 2024-09-12 Naoki Sato , Michio Yamada

The bold diagrammatic Monte Carlo (BDMC) method performs an unbiased sampling of Feynman's diagrammatic series using skeleton diagrams. For lattice models the efficiency of BDMC can be dramatically improved by incorporating dynamic…

Statistical Mechanics · Physics 2015-05-20 L. Pollet , N. V. Prokof'ev , B. V. Svistunov

High-fidelity Monte Carlo simulations and complex inverse problems, such as mapping smeared experimental observations to ground-truth states, are computationally intensive yet essential for robust data analysis. Conditional Flow Matching…

Machine Learning · Computer Science 2026-04-03 Zeyu Xia , Tyler Kim , Trevor Reed , Judy Fox , Geoffrey Fox , Adam Szczepaniak

The growth of computational resources in the past decades has expanded the application of Computational Fluid Dynamics (CFD) from the traditional fields of aerodynamics and hydrodynamics to a number of new areas. Examples range from the…

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

Diffuse interface descriptions offer many advantages for the modeling of microstructure evolution. However, the numerical representation of moving diffuse interfaces on discrete numerical grids involves spurious grid friction, which limits…

Materials Science · Physics 2022-09-21 Michael Fleck , Felix Schleifer , Patrick Zimbrod

Using direct simulations, weakly nonlinear theory and nonlinear mean-field theory, it is shown that the quenched velocity field of a saturated nonlinear dynamo can itself act as a kinematic dynamo. The flow is driven by a forcing function…

Astrophysics · Physics 2008-11-21 Andreas Tilgner , Axel Brandenburg

We re-examine the nature of the turbulent magnetic diffusivity tensor of mean field electrodynamics and show that an inconsistency arises if it is calculated via consideration of time-independent magnetic fields. Specifically, the predicted…

Solar and Stellar Astrophysics · Physics 2010-01-14 David W. Hughes , Michael R. E. Proctor

By performing ideal magnetohydrodynamical (MHD) simulations with weak vertical magnetic fields in unstratified cylindrical shearing boxes with modified boundary treatment, we investigate MHD turbulence excited by magnetorotational…

High Energy Astrophysical Phenomena · Physics 2023-11-06 Takeru K. Suzuki

The mean electromotive force and alpha effect are computed for a forced turbulent flow using a simple nonlinear dynamical model. The results are used to check the applicability of two basic analytic ansatze of mean-field…

Astrophysics · Physics 2009-01-25 V. V. Pipin , M. R. E. Proctor

Modern machine learning (ML) models of chemical and materials systems with billions of parameters require vast training datasets and considerable computational efforts. Lightweight kernel or decision tree based methods, however, can be…

Chemical Physics · Physics 2024-10-18 Danish Khan , O. Anatole von Lilienfeld
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