A fast algorithm for particle simulations
Journal of Computational Physics
The fast Fourier transform and its applications
The fast Fourier transform and its applications
Multilevel matrix multiplication and fast solution of integral equations
Journal of Computational Physics
SIAM Journal on Scientific Computing
Multipole translation theory for the three-dimensional Laplace and Helmholtz equations
SIAM Journal on Scientific Computing
3D Impact and Toroidal Bubbles
Journal of Computational Physics
IES3: Efficient Electrostatic and Electromagnetic Simulation
IEEE Computational Science & Engineering
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Journal of Computational Physics
A fast algorithm for modeling multiple bubbles dynamics
Journal of Computational Physics
A precorrected-FFT method for electrostatic analysis of complicated 3-D structures
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A fast algorithm for modeling multiple bubbles dynamics
Journal of Computational Physics
Hi-index | 31.45 |
This work presents the development of a numerical strategy that combines the fast Fourier transform on multipoles (FFTM) method and the boundary element method (BEM) to study the physics of multiple bubbles dynamics in moving boundary problems. The recent FFTM method can be employed to speedup the resolution of the boundary integral equation. However, one major drawback of the method is that its efficiency deteriorates quite significantly when the problem is spatially sparsely populated, as in the case where multiple bubbles are well separated. To overcome this deficiency, a new version of FFTM with clustering is proposed (henceforth called FFTM Clustering). The new algorithm first identifies and groups closely positioned bubbles. The original FFTM is then used to compute the potential contributions from the bubbles within its own group, while contributions from the other separated groups are evaluated via the multipole to local expansions translations operations directly. We tested the FFTM Clustering on several multiple bubble examples to demonstrate its effectiveness over the original FFTM method and vast improvement over the standard BEM. The high efficiency of the FFTM Clustering method allows us to simulate much larger multiple bubbles dynamics problems within reasonable time. Some physical behaviors of the multiple bubbles are also presented in this work.