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jerabaul29 avatar jerabaul29 commented on July 19, 2024

Hi!

A few notes:

  • It looks like some other things were also modified in the simulation (if I am not wrong?), because the value of the drag is much lower than anything I have seen before. Did you add some jets that can perform blowing, modify some other parameters, changed the Reynolds number, or something else? ;) (note that if you are doing some form of research using the code you do not really need to give me a specific answer, but I would be interested to get confirmation that you also modified some other stuff).

  • There are many parameters that can influence the duration of the simulation, as the simulation can stop either using the maximum number of control flag (nb_actuations here):

runner.run(episodes=2000, max_episode_timesteps=nb_actuations, episode_finished=episode_finished)

or the terminal condition itself:

terminal = False
if self.verbose > 2:
printiv(terminal)
reward = self.compute_reward()
if self.verbose > 2:
printiv(reward)
if self.verbose > 1:
printi("--- done execute ---")
return(next_state, terminal, reward)

I think in this version of the code, we always set terminal to False, so the simulation never ends because of the terminal flag in the execute function, but always instead because of hitting the max_episode_timesteps in the runner.

Note that the max_episode_timesteps value is related to the number of steps, but this is not a 1 to 1 correspondance as the network does not update the control at each time step:

for _ in range(self.number_steps_execution):

Does that make sense? :)

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jerabaul29 avatar jerabaul29 commented on July 19, 2024

PS: Ok, I guess by 'extending the simulation area' you may mean 'making it wider', then this may explain for the change in drag coefficient ;)

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yangtianyong avatar yangtianyong commented on July 19, 2024

Yes,I mean make it wider.And,those parameters you talked about can explain my confusion!
Thank you!

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jerabaul29 avatar jerabaul29 commented on July 19, 2024

Ok. The code is a bit messy, you may need to fix / rewrite some parts to make it more fitted to cases outside of the two cases we shipped.

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jerabaul29 avatar jerabaul29 commented on July 19, 2024

By the way, I am a bit curious about what you want to use our code for. Are you a student / researcher / other? If you want more detailed help and comments we can discuss about a more formal collaboration / working together on something. Of course I perfectly understand if you are not interested / this does not fit you.

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yangtianyong avatar yangtianyong commented on July 19, 2024

Hello,I am a student .The main purpose that use your code is to learn Deep reinforcement learning.I mean,you are the first time to use deep neural networks and reinforcement learning to the field of active flow control.And I want to know the details how reinforcement learning to train deep neural networks.Moreover,how does the code achieve those.
yes,I am interested in this work,also I want to use this idea to something else.However,I am a new learner of this field,and I normally feel confused to learn Deep reinforcement learning,case it's to difficult for me ,and few material to get!
Still,thank you for your help all the time!

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jerabaul29 avatar jerabaul29 commented on July 19, 2024

That sounds good! Good luck with your applications, hope you get successful! No worries, happy to help DRL diffuse to other people!

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jerabaul29 avatar jerabaul29 commented on July 19, 2024

PS: are you a PhD student or masters student or other? :)

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yangtianyong avatar yangtianyong commented on July 19, 2024

A masters student (my work maybe involved this field),you are really good at the Deep reinforcement learning.Would you have any great suggestions to learn about it?

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jerabaul29 avatar jerabaul29 commented on July 19, 2024

I am not that good, but I am trying to be ^^

Have you been through the materials here?

https://github.com/jerabaul29/Cylinder2DFlowControlDRL/blob/master/LearningMaterial/README.md

Otherwise mostly googling around, reading code and ArXiv papers should help you.

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yangtianyong avatar yangtianyong commented on July 19, 2024

yes ,I have been read those materials .In addition ,I usually surf the Internet to search some
basic knowledge(but can't form a system).

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jerabaul29 avatar jerabaul29 commented on July 19, 2024

Good!

Yes, the field is very new so information is still scattered. This is both the exciting and the annoying part about working in a novel, modern, booming field.

Closing this issue as it seems everything is working as you want now.

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