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For a magnetised plasma in a straight magnetic guide field, we derive a set of four-dimensional kinetic equations, which can capture electromagnetic turbulence in the drift kinetic limit. To do so, we start from the gyrokinetic equations,…

Plasma Physics · Physics 2022-03-09 Evgeny A. Gorbunov , Bogdan Teaca

Numerical simulation of fluids plays an essential role in modeling many physical phenomena, such as weather, climate, aerodynamics and plasma physics. Fluids are well described by the Navier-Stokes equations, but solving these equations at…

Fluid Dynamics · Physics 2022-04-27 Dmitrii Kochkov , Jamie A. Smith , Ayya Alieva , Qing Wang , Michael P. Brenner , Stephan Hoyer

The transition from laminar to turbulent flow is an immensely important topic that is still being studied. Here we show that complex plasmas, i.e., microparticles immersed in a low temperature plasma, make it possible to study the…

Plasma Physics · Physics 2024-01-30 Eshita Joshi , Markus H Thoma , Mierk Schwabe

Drift ordered fluid models are widely applied in studies of low-frequency turbulence in the edge and scrape-off layer regions of magnetically confined plasmas. Here, we show how collisional transport across the magnetic field is…

Plasma Physics · Physics 2016-04-15 Jens Madsen , Volker Naulin , Anders Henry Nielsen , Jens Juul Rasmussen

The plasma edge of a tokamak configuration is characterized by turbulent dynamics leading to enhanced transport. We construct a simplified 3D Hasegawa--Wakatani model reducing to a single partial differential equation for the turbulent…

Plasma Physics · Physics 2023-09-13 Nakia Carlevaro , Giovanni Montani , Fabio Moretti

Plasma turbulence is a key challenge in understanding transport phenomena in magnetically confined plasmas. This work presents a novel approach using periodic orbit theory to analyze plasma turbulence, identifying fundamental structures…

Plasma Physics · Physics 2025-09-12 Sidney D. V. Williams , Matthew N. Gudorf , Dmitri M. Orlov

We investigate the utility of deep learning for modeling the clustering of particles that are aerodynamically coupled to turbulent fluids. Using a Lagrangian particle module within the Athena++ hydrodynamics code, we simulate the dynamics…

Earth and Planetary Astrophysics · Physics 2024-01-09 Yan-Mong Chan , Natascha Manger , Yin Li , Chao-Chin Yang , Zhaohuan Zhu , Philip J. Armitage , Shirley Ho

Predicting the evolution of turbulent flows is central across science and engineering. Most studies rely on simulations with turbulence models, whose empirical simplifications introduce epistemic uncertainty. The Eigenspace Perturbation…

Machine Learning · Computer Science 2025-11-11 Minghan Chu , Weicheng Qian

Serrations are commonly employed to mitigate the turbulent boundary layer trailing-edge noise. However, significant discrepancies persist between model predictions and experimental observations. In this paper, we show that this results from…

Fluid Dynamics · Physics 2023-12-27 Haopeng Tian , Benshuai Lyu

Simulating spatiotemporal turbulence with high fidelity remains a cornerstone challenge in computational fluid dynamics (CFD) due to its intricate multiscale nature and prohibitive computational demands. Traditional approaches typically…

Fluid Dynamics · Physics 2024-07-01 Xiantao Fan , Deepak Akhare , Jian-Xun Wang

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

The edge density and temperature of tokamak plasmas are strongly correlated with energy and particle confinement and their quantification is fundamental to understanding edge dynamics. These quantities exhibit behaviours ranging from sharp…

Plasma Physics · Physics 2022-01-05 Abhilash Mathews , Jerry Hughes

Turbulent transport remains one of the principal obstacles to achieving efficient magnetic confinement in fusion devices. Two of the dominant drivers of the turbulence are microscale instabilities fuelled by electron- and ion-temperature…

Particle transport, acceleration and energisation are phenomena of major importance for both space and laboratory plasmas. Despite years of study, an accurate theoretical description of these effects is still lacking. Validating models with…

Kinetic-range turbulence in magnetized plasmas and, in particular, in the context of solar-wind turbulence has been extensively investigated over the past decades via numerical simulations. Among others, one of the widely adopted reduced…

Plasma Physics · Physics 2017-05-24 S. S. Cerri , L. Franci , F. Califano , S. Landi , P. Hellinger

In many plasma systems, introducing a small background shear flow is enough to stabilize the system linearly. The nonlinear dynamics are much less sensitive to sheared flows than the average linear growthrates, and very small amplitude…

Plasma Physics · Physics 2018-01-17 Chris C. T. Pringle , Ben F. McMillan , Bogdan Teaca

Two-fluid Braginskii codes have simulated open-field line turbulence for over a decade, and only recently has it become possible to study these systems with continuum gyrokinetic codes. This work presents a first-of-its-kind comparison…

In strong electromagnetic fields, unique plasma phenomena and applications emerge, whose description requires recently developed theories and simulations [Y. Shi, Ph.D. thesis, Princeton University (2018)]. In the classical regime, to…

Plasma Physics · Physics 2021-04-21 Yuan Shi , Hong Qin , Nathaniel J. Fisch

Microturbulence can produce stationary fine-scale radial corrugations on the plasma density and temperature gradients in magnetic confinement fusion devices. We show that these structures play a significant role in regulating turbulent…

Plasma Physics · Physics 2025-07-22 Ajay C. J , M. J. Pueschel , Justin Ball , David Hatch , Tobias Goerler , Stephan Brunner

Magnetic geometry has a significant effect on the level of turbulent transport in fusion plasmas. Here, we model and analyze this dependence using multiple machine learning methods and a dataset of > 200,000 nonlinear simulations of…