Hadi Pouransari

The Inverse Fast Multipole Method: Using a Fast Approximate Direct Solver as a Preconditioner for Dense Linear Systems

Although some preconditioners are available for solving dense linear systems, there are still many matrices for which preconditioners are lacking, in particular in cases where the size of the matrix

Optimizing the Adaptive Fast Multipole Method for Fractal Sets

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Fast Hierarchical Solvers For Sparse Matrices Using Extended Sparsification and Low-Rank Approximation

becomes very large. There remains hence a great need to develop general purpose preconditioners whose cost scales well with the matrix size

A distributed-memory hierarchical solver for general sparse linear systems

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Settling of heated particles in homogeneous turbulence

. In this paper, we propose a preconditioner with broad applicability and with cost

Parallel variable-density particle-laden turbulence simulation

\mathcal{O}(N)

Effects of Preferential Concentration on Heat Transfer in Particle-Based Solar Receivers

for dense matrices, when the matrix is given by a smooth kernel. Extending the method using the same framework to general

Particle-laden flows forced by the disperse phase: Comparison between Lagrangian and Eulerian simulations

\mathcal{H}^2

Fast hierarchical solvers for sparse matrices

-matrices is relatively straightforward. These preconditioners have a controlled accuracy (machine accuracy can be achieved if needed) and scale linearly with

Spectral analysis of energy transfer in turbulent flows laden with heated particles

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