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Solving the stochastic Burgers equation with a sensitivity derivative-driven Monte Carlo method
Version 2 2016-09-16, 15:12
Version 1 2016-09-16, 14:52
dataset
posted on 2016-09-16, 15:12 authored by paul.hauseux@uni.lu, Jack S. HaleJack S. Hale, Stéphane BORDASStéphane BORDASCode to solve a 1D stochastic viscous Burgers equation using a sensitivity derivative-driven Monte Carlo method. A Docker image is provided that can run all of the included code.
This code generates the figures shown in the paper:
Accelerating Monte Carlo estimation with derivatives of high-level finite element models, P. Hauseux, J.S. Hale, S.P.A. Bordas. 1 May 2017. 318, pp. 917-936. Computer Methods in Applied Mechanics and Engineering.
http://dx.doi.org/10.1016/j.cma.2017.01.041
http://hdl.handle.net/10993/28618
This figshare repository is for archival purposes. It is easiest to use the code and image directly from the Bitbucket and Dockerhub repositories shown in the References section below. Full instructions are given in the README.md file inside the code archive file.
The code is licensed under the LGPL v3.0.
The Docker image contains binaries for a variety of open source software. All software binaries in the container were compiled from unmodified sources from the project originators.
