Project : Reactor Design and Analysis (Fusion Reactor Technology 1)

Introduction

This is a git repository of python codes for designing fusion reactors. Based on the reference, it is possible to determine the plasma parameters and reactor design by using this code. If basic quantities are determined, the reactor parameters can be computed and it is able to check the validity of the tokamak design.

How to execute

Computation of the desired tokamak design

• Exectue main.py with modifying the configuration of the device in config/device_info.py
• You can print the detail of the tokamak design and its performance from Lawson criteria

      python3 main.py --save_dir {directory name} --tag {tag name}
  

Find the optimal tokamak design with reinforcement learning

• We use (1) Gridserach, (2) Genetic algorithm, and (3) Reinforcement learning algorithm for design optimization.
• In the case of RL, we use single-step PPO algorithm to find out the optimal tokamak design which satisfies operation limits
• We designed the optimal tokamak which achieves high energy confinement while satisfying minimum cost (=size of tokamak).
• You can execute 3 different design optmization codes as below.

1. Gridsearch

    python3 find_gridsearch.py --blanket_type {'solid' or 'liquid'} --num_episode {# of episodes} --n_grid {# of grids}

2. Deep Reinforcement Learning

    python3 find_drl.py --blanket_type {'solid' or 'liquid'} --num_episode {# of episodes} --buffer_size {buffer size} --lr {learning rate}

Design optimization result based on RL

We use the initial configuration of the tokamak from the grid search algorithm to find out the naive solution which satisfies the conditions for operation limit. Using single-step PPO algorithm, we can obtain the optimal design configuration of the tokamak which satisfies both the conditions and minimum cost condition. This optimal solution even satisfies that the performance is greater than Q = 10.

• Lawson criteria

• Overall performance

Reference

• Designing a tokamak fusion reactor : How does plasma physics fit in? (J.P.Freidberg, F.J.Mangiarotti, J.Minervini, Physics of plasmas, 2015)
• Spectial topics on fusion reactor enigneering, Jisung Kang, KFE
• Lecture note on Fusion Reactor Technology 1, Yong-su Na, SNU
• Direct shape optimization through deep reinforcement learning, Jonathan Viquerat et al