Control of the number of particles in fluid and MHD particle in cell methods
Reference (16)
J. Comput. Phys.
(1991)- et al.
J. Comput. Phys.
(1992) Comput. Phys. Commun.
(1987)- et al.
J. Comput. Phys.
(1986) J. Comput. Phys.
(1991)- et al.
J. Comput. Phys.
(1994) J. Meteor. Soc. Japan
(1982)- et al.
Mon. Wea. Rev.
(1985)
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Explicit energy-conserving modification of relativistic PIC method
2024, Journal of Computational PhysicsA dynamical particle merging and splitting algorithm for Particle-In-Cell simulations
2024, Computer Physics CommunicationsAgnostic conservative down-sampling for optimizing statistical representations and PIC simulations
2022, Computer Physics CommunicationsStrategies for particle resampling in PIC simulations
2021, Computer Physics CommunicationsCitation Excerpt :A way to perform thinning with conservation of several arbitrary particle and grid quantities is proposed in Ref. [15]. Within the approach of complete resampling, Lapenta and Brackbill proposed a method of replacing the macroparticles in a given cell with a new subset, preserving the contributions to the grid quantities and also maximizing the uniformity of the distribution of these quantities over the new subset [16]. A way of doing such resampling with the conservation of grid values for charge and current density, as well as of the total energy of the resampled macroparticles, has been proposed by Assous et al. [17] and further developed in Ref. [18].
Adaptive smoothing length method based on weighted average of neighboring particle density for SPH fluid simulation
2021, Virtual Reality and Intelligent HardwareMoment preserving constrained resampling with applications to particle-in-cell methods
2020, Journal of Computational PhysicsCitation Excerpt :However, because here we are concerned with a sample-based representation of a distribution function (f), the motivation is quite different. By minimizing the variance of the particle weights, we ensure that the particles carry near-maximum information about the distribution; whereas, in [23], the objective is to ensure a smooth representation of a continuous field. The motivation here is more closely related to the use of uniformly weighted samples in Monte Carlo methods.