Higher-order particle representation for particle-in-cell simulations

Brown, Dominic A.S.; Bettencourt, Matthew Tyler; Wright, Steven A.; Maheswaran, Satheesh; Jones, John P.; Jarvis, Stephen A.

doi:10.1016/j.jcp.2021.110255

Higher-order particle representation for particle-in-cell simulations

Journal Article · 07 March 2021 · Journal of Computational Physics

DOI:https://doi.org/10.1016/j.jcp.2021.110255· OSTI ID:1781539

Brown, Dominic A.S. ^[1]; Bettencourt, Matthew Tyler ^[2]; Wright, Steven A. ^[3]; Maheswaran, Satheesh ^[4]; Jones, John P. ^[5]; ^[6]

University of Warwick, (United Kingdom)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Univ. of York (United Kingdom)
Science and Technology Facilities Council (STFC), Oxford (United Kingdom). Diamond Light Source, Ltd.
Atomic Weapons Establishment (AWE), Aldermaston (United Kingdom)
Univ. of Birmingham (United Kingdom)

In this paper we present an alternative approach to the representation of simulation particles for unstructured electrostatic and electromagnetic PIC simulations. In our modified PIC algorithm we represent particles as having a smooth shape function limited by some specified finite radius, r₀. A unique feature of our approach is the representation of this shape by surrounding simulation particles with a set of virtual particles with delta shape, with fixed offsets and weights derived from Gaussian quadrature rules and the value of r₀. As the virtual particles are purely computational, they provide the additional benefit of increasing the arithmetic intensity of traditionally memory bound particle kernels. The modified algorithm is implemented within Sandia National Laboratories' unstructured EMPIRE-PIC code, for electrostatic and electromagnetic simulations, using periodic boundary conditions. We show results for a representative set of benchmark problems, including electron orbit, a transverse electromagnetic wave propagating through a plasma, numerical heating, and a plasma slab expansion. In this work, good error reduction across all of the chosen problems is achieved as the particles are made progressively smoother, with the optimal particle radius appearing to be problem-dependent.

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); Atomic Weapons Establishment (AWE)

Grant/Contract Number:: AC04-94AL85000; NA0003525

OSTI ID:: 1781539

Alternate ID(s):: OSTI ID: 1781531

Report Number(s):: SAND--2021-2070J; 693962

Journal Information:: Journal of Computational Physics, Journal Name: Journal of Computational Physics Vol. 435; ISSN 0021-9991

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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