A Python/Bempp-based plug-in for uncertainty quantification by random domains. Refer to: Helmholtz scattering by random domains: first-order sparse boundary element approximation
@article{escapil2020helmholtz,
title={Helmholtz scattering by random domains: first-order sparse boundary element approximation},
author={Escapil-Inchausp{\'e}, Paul and Jerez-Hanckes, Carlos},
journal={SIAM Journal on Scientific Computing},
volume={42},
number={5},
pages={A2561--A2592},
year={2020},
publisher={SIAM}
}
Includes:
- (FOA) Tutorials to evaluate the shape derivative for both sound-soft and sound-hard Helmholtz scattering problems
- (TP Main) Tutorial to solve the Transmission Problem (TP) and analyze the convergence of GMRES
- (Combination Technique) Implementation of the CT for the TP by the unit sphere (work in progress to adapt the structure to the docker version of bempp)
- (Tensor Operator Solver) Solve preconditioned tensor operator equations with GMRES
- projection.py Routines to evaluate the transfer operators between grids for P1 elements
- login.py Minor modifications of the original Bempp code
A Bempp Docker image is easily accessible at: https://bempp.com/download/docker/
Example of transformed boundaries respect to t meshed with 3,249 vertices
.