Hierarchical Block Low-rank Approximation of Cavity Radiation

05/11/2023
by   Ivan Baburin, et al.
0

In this paper we examine the use of low-rank approximations for the handling of radiation boundary conditions in a transient heat equation given a cavity radiation setting. The finite element discretization that arises from cavity radiation is well known to be dense, which poses difficulties for efficiency and scalability of solvers. Here we consider a special treatment of the cavity radiation discretization using a block low-rank approximation combined with hierarchical matrices. We provide an overview of the methodology and discusses techniques that can be used to improve efficiency within the framework of hierarchical matrices, including the usage of the approximate cross approximation (ACA) method. We provide a number of numerical results that demonstrate the accuracy and efficiency of the approach in practical problems, and demonstrate significant speedup and memory reduction compared to the more conventional "dense matrix" approach.

READ FULL TEXT

page 16

page 23

page 24

research
02/16/2023

Low-rank solutions to the stochastic Helmholtz equation

In this paper, we consider low-rank approximations for the solutions to ...
research
08/12/2022

Solving Linear Systems on a GPU with Hierarchically Off-Diagonal Low-Rank Approximations

We are interested in solving linear systems arising from three applicati...
research
03/27/2021

ℋ-matrix approximability of inverses of FEM matrices for the time-harmonic Maxwell equations

The inverse of the stiffness matrix of the time-harmonic Maxwell equatio...
research
02/15/2023

Efficient low rank approximations for parabolic control problems with unknown heat source

An inverse problem of finding an unknown heat source for a class of line...
research
05/10/2021

Dynamical low-rank approximation for Burgers' equation with uncertainty

Quantifying uncertainties in hyperbolic equations is a source of several...
research
05/30/2017

Sparse and low-rank approximations of large symmetric matrices using biharmonic interpolation

Symmetric matrices are widely used in machine learning problems such as ...
research
08/29/2020

Computing low-rank approximations of the Fréchet derivative of a matrix function using Krylov subspace methods

The Fréchet derivative L_f(A,E) of the matrix function f(A) plays an imp...

Please sign up or login with your details

Forgot password? Click here to reset