Mr. Jingzhe Zhu Profile

Jingzhe Zhu

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Proceedings Article | 1 April 2024 Paper

Analyzing fusion plasma diagnostic images based on computer vision and deep learning

Jingzhe Zhu, Qiyue Huang, Pan Liu, Zilong Yuan, Zhangchun Tang

Proceedings Volume 12987, 129870C (2024) https://doi.org/10.1117/12.3023470

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The analysis of inertial confinement fusion (ICF) plasma diagnostic pictures is crucial for fusion energy research. In this paper, a method based on the combination of deep reinforcement learning and computer vision techniques is proposed for the analysis of ICF plasma diagnostic pictures. The method first preprocesses the images using computer vision techniques and then uses deep reinforcement learning to classify and recognise them. The physical quantities are closer to the theoretical values using the new method, which is more instructive for the experiments. For example, at the radiation temperature, the obtained values are increased by 20-70 eV, and at the electron and plasma temperatures are close to the theoretical 5 KeV. at the same time the neutron yield is increased by a factor of 10. The experimental results show that the method has high accuracy and efficiency in the analysis of ICF plasma diagnostic pictures, and can effectively assist fusion research.

Proceedings Article | 27 March 2024 Paper

Fusion diagnostics based on blockchain technology

Jingzhe Zhu, Qiyue Huang, Pan Liu, Zilong Yuan, Zhangchun Tang, Gaoyang Liu, Ziqian Li

Proceedings Volume 13105, 131054C (2024) https://doi.org/10.1117/12.3026328

KEYWORDS: Blockchain, Diagnostics, Data fusion, Plasma diagnostics

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Nuclear fusion is a form of energy release that has received a lot of attention as it can free mankind from fossil fuels. However, the fusion process requires strict monitoring and measurement to ensure the reliability and safety of the reaction. Conventional fusion diagnostic devices suffer from problems such as low data credibility, data security and privacy protection, which may lead to inaccurate diagnostic results and thus threaten the stability and safety of the reaction. Therefore, how to solve these problems is an urgent issue at present. Blockchain technology is a distributed database technology, which has the characteristics of decentralisation, non-tampering and traceability. Blockchain technology has been widely used in finance, logistics, medical and other fields. In this paper, we will explore how to use blockchain technology to solve the problems of nuclear fusion diagnostic devices and improve the credibility and safety of nuclear fusion diagnosis. In this paper, a blockchain platform will be built to integrate mainly thermal imaging, mass spectrometer and neutron measurement data in fusion diagnostics. These data are stored on the blockchain using a consensus algorithm and establishing a multi-node mechanism. This prevents the data from being tampered with and can be traced at the same time. In terms of processing speed, due to the centralization and unification of the data and the nature of the consensus algorithm, the speed of processing data can be increased by several orders of magnitude through blockchain technology.

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