Hadi Pouransari — Page 3

arXiv2016

Parallel variable-density particle-laden turbulence simulation

We have developed a fully parallel C++/MPI based simulation code for variable-density particle-laden turbulent flows. The fluid is represented through a uniform Eulerian staggered grid, while particles are modeled using a Lagrangian point-particle framework. Spatial discretization is second-order accurate, and time integration has a fourth-order accuracy. Two-way coupling of the particles with the background flow is considered in both momentum and energy equations. The code is fully modular and abstracted, and easily can be extended or modified. We have considered two different boundary conditions. We have also developed a novel parallel linear solver for the variable density Poisson equation that arises in the calculation.

physics.comp-ph↗

arXiv2015

Optimizing the adaptive fast multipole method for fractal sets

We have performed a detailed analysis of the fast multipole method (FMM) in the adaptive case, in which the depth of the FMM tree is non-uniform. Previous works in this area have focused mostly on special types of adaptive distributions, for example when points accumulate on a 2D manifold or accumulate around a few points in space. Instead, we considered a more general situation in which fractal sets, e.g., Cantor sets and generalizations, are used to create adaptive sets of points. Such sets are characterized by their dimension, a number between 0 and 3. We introduced a mathematical framework to define a converging sequence of octrees, and based on that, demonstrated how to increase $N \to \infty$. A new complexity analysis for the adaptive FMM is introduced. It is shown that the ${\cal{O}}(N)$ complexity is achievable for any distribution of particles, when a modified adaptive FMM is exploited. We analyzed how the FMM performs for fractal point distributions, and how optimal parameters can be picked, e.g., the criterion used to stop the subdivision of an FMM cell. A new subdividing double-threshold method is introduced, and better performance demonstrated. Parameters in the FMM are modeled as a function of particle distribution dimension, and the optimal values are obtained. A three dimensional kernel independent black box adaptive FMM is implemented and used for all calculations.

math.NA↗