Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Euler Equations - Sod Problem - Shock Capturing Issue #126

Closed
alexpapados opened this issue Sep 24, 2020 · 3 comments
Closed

Euler Equations - Sod Problem - Shock Capturing Issue #126

alexpapados opened this issue Sep 24, 2020 · 3 comments

Comments

@alexpapados
Copy link

Hello!

I hope all is well.

I need some advice on how to obtain better results for the Sod problem. I have looked through the FAQ on how to train the network better when training fails. I've introduced loss weights, increased the number of points in the domain and increased the number of iterations. Unfortunately, I am not able to capture the proper solutions to this problem. Each solution to rho,u, and p experiences too much dissipation or solutions have random jumps. I have attached my code below. Any advice moving forward would be greatly appreciated.

Euler_Eq.py.zip

@lululxvi
Copy link
Owner

Euler Equation is not easy to learn because of the shock. You may try put more points near the shock, see https://doi.org/10.1016/j.cma.2019.112789

@kmache
Copy link

kmache commented Jun 13, 2023

Dear Lu Lu
Please I am also working on PDEs with shock, how can I put more points near the shock? can you provide a piece of code?

@lululxvi
Copy link
Owner

See FAQ Q: How does DeepXDE choose the training points? How can I use some specific training points?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants