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In this paper, a finite volume lattice Boltzmann method (FVLBM) based on cell-center unstructured girds is presented and full studied to simulate the incompressible laminar flows, which is simple modified from the cell-vertex unstructured…

Computational Physics · Physics 2018-12-04 Yong Wang , Chengwen Zhong , Jun Cao , Congshan Zhuo

Fluid-particle systems are very common in many natural processes and engineering applications. However, accurately and efficiently modelling fluid-particle systems with complex particle shapes is still a challenging task. Here, we present a…

Fluid Dynamics · Physics 2023-03-22 Pei Zhang , Ling Qiu , S. A. Galindo-Torres , Yilin Chen , A. Scheuermann , Ling Li

Reliable position and shape control in tokamak plasmas requires accurate real-time regulation of several strongly coupled shape parameters. The control vectors that disentangle these couplings, referred to as \textit{virtual circuits}…

In this paper, we develop a three-dimensional multiple-relaxation-time lattice Boltzmann method (MRT-LBM) based on a set of non-orthogonal basis vectors. Compared with the classical MRT-LBM based on a set of orthogonal basis vectors, the…

Fluid Dynamics · Physics 2023-06-29 Linlin Fei , Jingyu Du , Kai H. Luo , Sauro Succi , Marco Lauricella , Andrea Montessori , Qian Wang

A new magnetohydrodynamics (MHD) code based on initial value approach, GMEC_I, has been developed for simulating various MHD physics in tokamak plasmas, as the MHD foundation of the gyrokinetic-MHD energetic particle simulation code (GMEC)…

Plasma Physics · Physics 2024-02-15 P. Y. Jiang , Z. Y. Liu , S. Y. Liu , J. Bao , G. Y. Fu

The immersed boundary method (IB) is an elegant way to fully couple the motion of a fluid and deformations of an immersed elastic structure. In that vein, the IB2d software allows for expedited explorations of fluid-structure interaction…

Fluid Dynamics · Physics 2018-09-19 Nicholas Battista , Christopher Strickland , Aaron Barrett , Laura Miller

It is well known that the number of particles should be scaled up to enable industrial scale simulation. The calculations are more computationally intensive when the motion of the surrounding fluid is considered. Besides the advances in…

Computational Physics · Physics 2014-07-28 Hao Zhang , F. Xavier Trias , Assensi Oliva , Dongmin Yang , Yuanqiang Tan , Shi Shu , Yong Sheng

Lattice Boltzmann method (LBM) is particularly well-suited for implementation on quantum circuits owing to its simple algebraic operations and natural parallelism. However, most quantum LBMs fix $\tau$ = 1 to avoid nonlinear collision,…

Quantum Physics · Physics 2025-05-19 Yang Xiao , Liming Yang , Chang Shu , Yinjie Du , Hao Dong , Jie Wu

In this work, using solutions from a local gyrokinetic flux-tube code combined with higher order ballooning theory, a new analytical approach is developed to reconstruct the global linear mode structure with associated global mode…

Plasma Physics · Physics 2017-10-18 P. A. Abdoul , D. Dickinson , C. M. Roach , H. R. Wilson

Uncertainties and errors in magnetic equilibrium reconstructions are a wide-spread problem in interpreting experimental data measured in the tokamak edge. This study demonstrates errors in EFIT++ reconstructions performed on the COMPASS…

Plasma Physics · Physics 2020-01-29 K. Jirakova , O. Kovanda , J. Adamek , M. Komm , J. Seidl

Computational fluid dynamics is both a thriving research field and a key tool for advanced industry applications. The central challenge is to simulate turbulent flows in complex geometries, a compute-power intensive task due to the large…

In recent years, the nonlinear 3D magnetohydrodynamic codes JOREK, M3D-C$^1$ and NIMROD developed the capability of modelling realistic 3D vertical displacement events (VDEs) including resistive walls. In this paper, a comprehensive 3D VDE…

Plasma Physics · Physics 2021-06-16 F. J. Artola , C. R. Sovinec , S. C. Jardin , M. Hoelzl , I. Krebs , C. Clauser

We present a novel, hardware-agnostic implementation strategy for lattice Boltzmann (LB) simulations, which yields massive performance on homogeneous and heterogeneous many-core platforms. Based solely on C++17 Parallel Algorithms, our…

Computational Physics · Physics 2021-05-11 Jonas Latt , Christophe Coreixas , Joël Beny

We propose a method for the data-driven inference of temporal evolutions of physical functions with deep learning. More specifically, we target fluid flows, i.e. Navier-Stokes problems, and we propose a novel LSTM-based approach to predict…

Machine Learning · Computer Science 2019-03-06 Steffen Wiewel , Moritz Becher , Nils Thuerey

Computational Fluid Dynamics (CFD) is a hugely important subject with applications in almost every engineering field, however, fluid simulations are extremely computationally and memory demanding. Towards this end, we present Lat-Net, a…

Machine Learning · Statistics 2017-05-26 Oliver Hennigh

A numerical method for simulation of bubble dynamics in three-dimensional potential flows is presented. The approach is based on the boundary element method for the Laplace equation accelerated via the fast multipole method implemented on a…

Computational Physics · Physics 2019-05-07 Nail A. Gumerov , Yulia A. Pityuk , Olga A. Abramova , Iskander S. Akhatov

Flux pumping was achieved in recent hybrid scenario experiments in the ASDEX Upgrade (AUG) tokamak, which is characterized by a sawtooth-free helical quiescent state and the anomalous radial redistribution of toroidal current density and…

Fusion power production in tokamaks uses discharge configurations that risk producing strong Type I Edge Localized Modes. The largest of these modes will likely increase impurities in the plasma and potentially damage plasma facing…

Plasma Physics · Physics 2022-12-20 Finn H. O'Shea , Semin Joung , David R. Smith , Ryan Coffee

Fluid flow simulation is a highly active area with applications in a wide range of engineering problems and interactive systems. Meshless methods like the Moving Particle Semi-implicit (MPS) are a great alternative to deal efficiently with…

Integration of machine learning (ML) models of unresolved dynamics into numerical simulations of fluid dynamics has been demonstrated to improve the accuracy of coarse resolution simulations. However, when trained in a purely offline mode,…

Fluid Dynamics · Physics 2023-07-26 Christian Pedersen , Laure Zanna , Joan Bruna , Pavel Perezhogin
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