Computer Physics Communications最新文献

This paper presents the new 2D electrostatic particle-in-cell code FENNECS developed to study the formation of magnetized non-neutral plasmas in geometries with azimuthal symmetry. This code has been developed in the domain of gyrotron electron gun design, but solves general equations and can be applied in other domains of plasma physics. FENNECS is capable of simulating electron-neutral collisions using a Monte Carlo approach and considers both elastic and inelastic (ionization) processes. It is also capable of solving the Poisson equation on domains with arbitrary geometries with either Dirichlet or natural boundary conditions. The Poisson solver is based on a meshless Finite Element Method, called web-splines, based on b-splines of any order, and used for the first time in the domain of plasma physics. In addition, the effect of fast ions colliding with the electrodes and causing ion induced electron emission at the electrode surfaces has been implemented in the code. In this paper, the governing equations solved by FENNECS and the numerical methods used to solve them are presented. A number of verification cases are then reported. Finally, the parallelization scheme used in FENNECS and its parallel scalability are presented.

Compressible particle-resolved direct numerical simulations (PR-DNS) are widely used in explosion-driven dispersion of particles simulations, multiphase turbulence modelling, and stage separation for two-stage-to-orbit vehicles. The direct forcing immersed boundary method (IBM) is a promising method and widely applied in low speed flow while there is few research regarding compressible flows. We developed a novel IBM to resolve supersonic and hypersonic gas flows interacting with irregularly shaped multi-body particle. The main innovation is that current method can solve the interaction of particles and high-speed fluids, particle translation and rotation, and collision among complex-shaped particles within a uniform framework. Specially, high conservation and computation consumption are strictly satisfied, which is critical for resolving the high speed compressible flow feature. To avoid the non-physical flow penetration around particle surface, an special iterative algorithm is specially derived to handle the coupling force between the gas and particles. The magnitude of the velocity difference error could be reduced by 6–8 orders compared to that of a previous method. Additionally, aerodynamic force integration was achieved using the momentum equation to ensure momentum conservation for two-phase coupling. A high-efficiency cell-type identification method for each step was proposed, and mapping among LPs and cells was used again to select the immersed cells. As for the collision force calculation, the complex shape of a particle was represented by a cloud of LPs and the mapping of LPs and cells was used to reduce the complexity of the algorithm for contact searching. The repetitive use of the mapping relationship could reduce the internal memory and improve the efficiency of the proposed algorithm. Moreover, various verification cases were conducted to evaluate the simulation performance of the proposed algorithm, including two- and three-dimensional moving and motionless particles with regular and complex shapes interacting with high-speed flow. Specifically, an experiment involving a shock passing through a sphere was designed and conducted to provide high-precision data. The corresponding results of the large-scale numerical simulation agree well with those obtained experimentally. The current method supports flow simulations at a particle-resolved scale in engineering.

ENDFtk is a recently developed C++ and Python interface to interact with ENDF-6 formatted nuclear data files. It provides a robust and complete interface, allowing the reading and writing of all formats currently part of the ENDF-6 formats manual, as well as some non-ENDF formats used by the NJOY processing code. It provides an interface that mimics the names in the ENDF-6 formats manual as well as an equivalent interface using human-readable attribute names. It is robust and powerful enogh for nuclear data experts to develop complex applications, while also simple enough to be used non-experts to retrieve and manipulate evaluated nuclear data. ENDFtk offers the ability to easily interrogate and manipulate data either in large-scale code projects or in simple Python scripts. In this paper, a brief overview of the interface is given, as well as more substantial examples demonstrating plotting simple data, interacting with more complex data, and writing new data to files. ENDFtk is open source and available for download via GitHub (https://github.com/njoy/ENDFtk).

Program summary

Program title: ENDFtk 1.0

CPC Library link to program files: https://doi.org/10.17632/9p4kxc2cvd.1

Developer's repository link: https://github.com/njoy/ENDFtk

Licensing provisions: BSD-3 clause

Programming language: C++ and Python

External routines/libraries: pybind11, ranges-v3, spdlog

Nature of problem: Provide an interface to read, write and manipulate nuclear data files using the ENDF-6 format. This interface can be integrated into other libraries requiring access to nuclear data, or be used directly using the Python interface.

Solution method: Library of C++ routines, with their Python bindings, to be integrated in higher-level codes and scripts

Particle pushers widely used in Particle-in-Cell(PIC) simulations are commonly required to be unconditionally stable and meet the basic physical laws. In this work, basing on central difference, we propose an unconditionally stable and well posed particle pusher. By mathematical deduction, the high-dimensional non-linear problem for solving tensor-form relativistic Lorentz force law equation is transformed to a quartic scalar problem and a following linear problem. Some practical suggestions for programming and some numerical results are also given.

FIRE is a program which performs integration-by-parts (IBP) reductions of Feynman integrals. Originally, the C++ version of FIRE relies on the computer algebra system Fermat by Robert Lewis to simplify rational functions. We present an upgrade of FIRE which incorporates a new library FUEL initially described in a separate publication, which enables a flexible choice of third-party computer algebra systems as simplifiers, as well as efficient communications with some of the simplifiers as C++ libraries rather than through Unix pipes. We achieve significant speedups for IBP reductions of Feynman integrals involving many kinematic variables, when using an open source backend based on FLINT newly added in this work, or the Symbolica backend developed by Ben Ruijl as a potential successor of FORM.

Program summary

Program title: FIRE, version 6.5 (FIRE 6.5)

CPC Library link to program files: https://doi.org/10.17632/cy6k69pb3y.2

Developer's repository link: https://gitlab.com/feynmanintegrals/fire.git

Licensing provisions: GPLv2

Programming language: Wolfram Mathematica 8.0 or higher, C++17

Supplementary material: See linked repository for installation instructions.

Journal reference of previous version: Comput. Phys. Commun. 247 (2020) 106877

Does the new version supersede the previous version?: Yes.

Reasons for the new version: The new version no longer relies on a single computer algebra system, Fermat [1], but instead allows a flexible choice of several systems, some of which offer higher performance, especially when the number of variables is large.

Summary of revisions: A new library FUEL [2] is used as a core component of the new version of FIRE to access different computer algebra systems as simplifiers of rational function expressions. Since the first release of FUEL described elsewhere, FUEL version 1.0 here has been enhanced with a new backend based on the open source library FLINT [3] that provides highly performant simplification of rational functions.

Nature of problem: Feynman integrals of a given family are reduced to a finite set of master integrals, by solving linear equations arising from integration by parts, using Gaussian elimination. The coefficients of the linear equations are generally rational functions in kinematic variables and the spacetime dimension, and the simplification of such rational functions during Gaussian elimination is a key task that is improved in this upgrade of FIRE.

Solution method: Computer algebra systems with state-of-the-art capabilities for polynomial GCD computations are used as simplification backends, or simp