Approximate Crank–Nicolson Algorithm with Higher-Order PML Implementation for Plasma Simulation in Open Region Problems
Author(s) -
Liqiang Niu,
Yongjun Xie,
Jie Gao,
Peiyu Wu,
Haolin Jiang
Publication year - 2021
Publication title -
international journal of antennas and propagation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.282
H-Index - 37
eISSN - 1687-5877
pISSN - 1687-5869
DOI - 10.1155/2021/6618492
Subject(s) - finite difference time domain method , crank–nicolson method , stability (learning theory) , convolution (computer science) , piecewise , algorithm , perfectly matched layer , piecewise linear function , computer science , scheme (mathematics) , order (exchange) , mathematics , mathematical analysis , physics , artificial intelligence , optics , finance , machine learning , artificial neural network , economics
By incorporating the higher-order concept with the perfectly matched later (PML) scheme, unconditionally stable approximate Crank–Nicolson algorithm is proposed for plasma simulation in open region problems. More precisely, the proposed implementation is based on the CN Direct-Splitting (CNDS) procedure for the finite-difference time-domain (FDTD) unmagnetized plasma simulation. The unmagnetized plasma can be regarded as frequency-dependent media which can be calculated by the piecewise linear recursive convolution (PLRC) method. The proposed implementation shows the advantages of higher-order concept, CNDS procedure, and PLRC method in terms of improved absorbing performance, enhanced computational efficiency, and outstanding calculation accuracy. Numerical examples are introduced to indicate the effectiveness and efficiency. It can be concluded from results that the proposed scheme shows considerable efficiency, accuracy, absorption, and unconditional stability.
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