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Ion temperature gradient control using reinforcement learning technique
https://repo.qst.go.jp/records/82462
https://repo.qst.go.jp/records/82462f78e0b99-d241-481a-8456-b778355e80b1
| Item type | 学術雑誌論文 / Journal Article(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2021-03-25 | |||||
| タイトル | ||||||
| タイトル | Ion temperature gradient control using reinforcement learning technique | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | journal article | |||||
| アクセス権 | ||||||
| アクセス権 | metadata only access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
| 著者 |
Takuma, Wakatsuki
× Takuma, Wakatsuki× Takahiro, Suzuki× Naoyuki, Oyama× Nobuhiko, Hayashi× Takuma, Wakatsuki× Takahiro, Suzuki× Naoyuki, Oyama× Nobuhiko, Hayashi |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Plasma with an internal transport barrier (ITB) is desirable for a steady-state tokamak reactor because of its high confinement quality and high bootstrap current fraction. However, the local pressure gradient tends to be steep and the plasma often becomes unstable. In this study, an ion temperature gradient control system based on neutral beam injection (NBI) is developed using the reinforcement learning technique. The response characteristics of an ion temperature gradient to NBI are non-linear and sensitive to experimental conditions, which makes it difficult to develop a robust control system. Our control system is trained for plasmas with a wide range of ITB strengths. Using the reinforcement learning technique, the system acquires a robust control feature through several thousand iterations of trial and error in an integrated transport simulation hosted by TOPICS. The control system is composed of neural networks (NNs) whose input variables are the ion temperature gradient, the current NBI power, and the NBI powers for several previous control time steps. The trained system can determine a control output which is suitable for the response characteristics inferred from the input variables. The trained control system is tested in the TOPICS simulation using plasma models based on two experimental plasmas of JT-60U with different ITB strengths. It is shown that the ion temperature gradient can be appropriately controlled for both plasmas, which supports the expectation that this system is applicable to real experiments. | |||||
| 書誌情報 |
Nuclear Fusion 巻 61, 号 4, p. 046036, 発行日 2021-03 |
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| 出版者 | ||||||
| 出版者 | IoP Publishing, International Atomic Energy Agency, EURATOM | |||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 0029-5515 | |||||
| DOI | ||||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | 10.1088/1741-4326/abe68d | |||||
| 関連サイト | ||||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | https://doi.org/10.1088/1741-4326/abe68d | |||||
