A new Particle-in-Cell method for modeling magnetized fluids

Bacchini, Fabio; Olshevsky, Vyacheslav; Poedts, Stefaan; Lapenta, Giovanni

doi:10.1016/j.cpc.2016.10.001

Cited by 6 publications

(10 citation statements)

References 46 publications

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“…Both MPM and CIC delivered impressive new results and are further developing; we refer the reader to the reviews of the applications of CIC in space plasma modeling (Lapenta, 2012); MPM in geophysics (Sulsky et al, 2007;Fatemizadeh and Moormann, 2015), engineering (York et al, 2000), and 3D graphics (Stomakhin et al, 2013). Motivated by the above success we proposed a new PIC algorithm for magnetized fluids (Bacchini et al, 2017) which clarified and simplified many aspects of the original FLIP-MHD algorithm by Brackbill (1991). This article discusses the realization of our algorithm, Slurm, implemented in C++ with OpenMP multi-threading.…”

Section: Motivationmentioning

confidence: 99%

“…Using vector potential as a proxy for magnetic field, on a staggered grid (Yee lattice), the ∇ · B = 0 condition is satisfied to machine precision (Bacchini et al, 2017). The staggered grid also makes our method second-order accurate in space.…”

Section: Magnetic Field Equationmentioning

confidence: 99%

“…These are interpolated onto 8 vertices (nodes) of the cell which encloses this particle. To compute interpolation weights, the conventional first order bspline is used as described in Bacchini et al (2017)…”

Section: 1mentioning

confidence: 99%

“…The velocity gradient is used to advance the particle's volume according to either the strategy described by Bacchini et al (2017), or in a simpler way:…”

Section: Steps 3 and 4 Interpolate On And Push The Particlesmentioning

confidence: 99%

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Slurm: Fluid particle-in-cell code for plasma modeling

Olshevsky

Bacchini

Poedts

et al. 2019

Computer Physics Communications

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With the approach of exascale computing era, particle-based models are becoming the focus of research due to their excellent scalability. We present a new code, Slurm, which implements the classic particle-in-cell algorithm for modeling magnetized fluids and plasmas. It features particle volume evolution which damps the numerical finite grid instability, and allows modeling of key physical instabilities such as Kelvin-Helmholtz and Rayleigh-Taylor. The magnetic field in Slurm is handled via the electromagnetic vector potential carried by particles. Numerical diffusion of the magnetic flux is extremely low, and the solenoidality of the magnetic field is preserved to machine precision. A double-linked list is used to carry particles, thus implementation of open boundary conditions is simple and efficient. The code is written in C++ with OpenMP multi-threading, and has no external dependencies except for Boost. It is easy to install and use on multi-core desktop computers as well as on large shared-memory machines. Slurm is an ideal tool for its primary goal, modeling of space weather events in the heliosphere. This article walks the reader through the physical model, the algorithm, and all important details of implementation. Ideally, after finishing this paper, the reader should be able to either use Slurm for solving the desired problem, or create a new fluid PIC code.

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Section: Motivationmentioning

confidence: 99%

Section: Magnetic Field Equationmentioning

confidence: 99%

Section: 1mentioning

confidence: 99%

“…The velocity gradient is used to advance the particle's volume according to either the strategy described by Bacchini et al (2017), or in a simpler way:…”

Section: Steps 3 and 4 Interpolate On And Push The Particlesmentioning

confidence: 99%

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Slurm: Fluid particle-in-cell code for plasma modeling

Olshevsky

Bacchini

Poedts

et al. 2019

Computer Physics Communications

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“…The fluid PIC method was first developed in the Sixties by Harlow to solve the fluid equations by advecting fluid quantities (mass, momentum, and energy) with computational particles [1]. New fluid PIC schemes were developed to decrease numerical diffusion and to solve plasma and material science problems [2,3]. In particular, the fluid PIC method eventually merged with the Material Point Method for simulating continuous materials [4].…”

Section: Introductionmentioning

confidence: 99%

PolyPIC: The Polymorphic-Particle-in-Cell Method for Fluid-Kinetic Coupling

et al. 2018

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Particle-in-Cell (PIC) methods are widely used computational tools for fluid and kinetic plasma modeling. While both the fluid and kinetic PIC approaches have been successfully used to target either kinetic or fluid simulations, little was done to combine fluid and kinetic particles under the same PIC framework. This work addresses this issue by proposing a new PIC method, PolyPIC, that uses polymorphic computational particles. In this numerical scheme, particles can be either kinetic or fluid, and fluid particles can become kinetic when necessary, e.g. particles undergoing a strong acceleration. We design and implement the PolyPIC method, and test it against the Landau damping of Langmuir and ion acoustic waves, two stream instability and sheath formation. We unify the fluid and kinetic PIC methods under one common framework comprising both fluid and kinetic particles, providing a tool for adaptive fluid-kinetic coupling in plasma simulations.

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Modeling of Heterogeneous Fluid Dynamics with Phase Transitions and Porous Media

SANDRAKOV

2024

Computational Methods and Mathematical Modeling in Cyberphysics and Engineering Applications 1

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A new Particle-in-Cell method for modeling magnetized fluids

Abstract: reference solutions and rather fast time and space convergence.

Cited by 6 publications

References 46 publications

Slurm: Fluid particle-in-cell code for plasma modeling

Slurm: Fluid particle-in-cell code for plasma modeling

PolyPIC: The Polymorphic-Particle-in-Cell Method for Fluid-Kinetic Coupling

Modeling of Heterogeneous Fluid Dynamics with Phase Transitions and Porous Media

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