等离子体装置运行控制模型
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当前可控核聚变面临的挑战和新型技术路线的尝试
2025-11-05 01:29
Summary of Key Points from Fusion Energy Conference Call Industry Overview - The conference call discusses the challenges and advancements in the field of controlled nuclear fusion, focusing on the commercialization of fusion energy and the various technological routes being explored [1][2][3]. Core Challenges in Controlled Nuclear Fusion - **Technical Challenges**: The primary challenges include the control of plasma for steady-state operation, the impact of high-energy neutron irradiation on materials, and the durability of high-temperature composite materials [2][4]. - **Material Limitations**: Current materials used in fusion reactors, such as tungsten alloys and low-activation steel, are not fully capable of withstanding the structural impacts caused by 14 MeV high-energy neutrons produced in deuterium-tritium reactions [2][3][4]. - **Tritium Fuel Cycle**: There is a significant lack of practical engineering experience regarding tritium cycling and storage, which poses a challenge for commercial fusion power plants [4][5]. Technological Routes and Innovations - **Mainstream Fusion Technologies**: The dominant fusion technology routes include magnetic confinement (e.g., tokamaks) and inertial confinement, with deuterium-tritium reactions being the most prevalent, accounting for 75% of current methods [3][4]. - **Emerging Technologies**: New routes such as hydrogen-boron (p-B11) and deuterium-helium-3 (D-He3) are gaining attention. Hydrogen-boron reactions produce no neutrons but require extremely high temperatures (30-50 billion degrees), while D-He3 reactions avoid neutron production but face challenges due to limited helium-3 availability [8][9]. Role of Artificial Intelligence - **AI Applications**: AI is being utilized in plasma control and material research. It aids in developing control models for plasma operation and accelerates the research of radiation-resistant materials and high-temperature superconductors [6][9]. - **Deep Learning in Plasma Control**: AI models can predict plasma disruptions and optimize magnetic field control for steady-state operation [6]. High-Temperature Superconductors - **Impact on Fusion Reactors**: High-temperature superconductors significantly reduce the size of fusion devices while increasing output. For instance, the U.S. CFS company has developed a 20 Tesla superconducting magnet and is constructing the Spark device, which is one-eighth the size of ITER but has a higher output [7]. - **Chinese Advancements**: Chinese teams, such as that led by Academician Wang Qiuliang, have achieved 25 Tesla, indicating significant progress in this area [7]. Global Developments in Fusion Energy - **International Progress**: The U.S. CFS company and DeepMind have made breakthroughs in high-temperature superconductors and AI applications in material science, respectively [9]. - **China's Contributions**: Since joining the ITER project in 2006, China has made substantial contributions in neutron-resistant materials and is actively working on engineering applications of fusion technologies [9]. Conclusion - The commercialization of controlled nuclear fusion is approaching but still faces significant technical challenges. Continued exploration of various technological routes and the integration of AI in research and development are crucial for overcoming these hurdles and achieving practical fusion energy solutions [3][4][9].