Machine Learning Applications Enabling Fusion Energy: Recent Developments

Cristina Rea

doi:10.1007/s10894-025-00509-z

2025-09-03

Cristina Rea *

DOI：10.1007/s10894-025-00509-z

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摘要

En 中文

在过去几年中，机器学习帮助开发了涵盖广泛领域的聚变能源先进能力。这包括从聚变诊断中提取信息的先进算法、用于等离子体状态估计与控制的增强算法、用于提高预测能力的加速模拟工具，以及用于聚变材料设计的扩展建模能力。本专题集合涵盖了机器学习应用研究的最新进展，进一步推动了聚变能源的发展路径；特别是它涵盖了广泛的聚变子领域——从惯性约束聚变到磁约束等离子体，包括高温超导磁体设计与优化。本社论总结了该集合内容，同时也提供了机器学习在未来如何被用于加速聚变能源作为可靠能源发展的关键展望。

Keyword:

Machine learning

Fusion

Technology

Open source

Benchmarks

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期刊

Journal of Fusion Energy

IF:

2.1

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