摘要详情
24 / 2023-03-30 21:27:23
Efficient designing laser profiles and target structures for laser-driven fusion
摘要录用
Laser-driven inertial confinement fusion is an important approach to achieve controllable nuclear fusion. It applies high-power laser pulses or X-rays to ablate outer surface of a spherical shell containing the fusion fuel, leading to a centripetal implosion and an increase in pressure and temperature of the fuel. In order to reach the Lawson criterion and thus realize a self-sustaining burning plasma, we have to compress the fuel to several hundred times of the solid density and rise the target temperature to over 5 keV.
Firstly, to realize an efficient implosion, the driven laser pulse and target structure are designed using a random walk method for a given laser energy. It can quickly optimize the laser pulse and target structure parameters for an efficient isentropic compression of the target. A correlation matrix can also be constructed to analyze the correlation between the parameters.
Secondly, we propose a hybrid optimization method by combining the random walk and the Bayesian methods, to further improve the optimization efficiency. The series of laser pulses and target structures that produces relatively high areal density obtained by the random walk optimization are used as the basic sampling data of the Bayesian optimization. It can greatly reduce the desired number of samples for Bayesian optimizations and the Bayesian optimization also makes up for the small step size and low efficiency of the random walk method in the later stage of optimization, and reduces the randomness in the optimization process. The hybrid optimization method greatly improves the optimization efficiency, and has been applied to the experiments of the Double-Cone ignition scheme. We believe that it will play a greater role in the future laser fusion experiments.
Firstly, to realize an efficient implosion, the driven laser pulse and target structure are designed using a random walk method for a given laser energy. It can quickly optimize the laser pulse and target structure parameters for an efficient isentropic compression of the target. A correlation matrix can also be constructed to analyze the correlation between the parameters.
Secondly, we propose a hybrid optimization method by combining the random walk and the Bayesian methods, to further improve the optimization efficiency. The series of laser pulses and target structures that produces relatively high areal density obtained by the random walk optimization are used as the basic sampling data of the Bayesian optimization. It can greatly reduce the desired number of samples for Bayesian optimizations and the Bayesian optimization also makes up for the small step size and low efficiency of the random walk method in the later stage of optimization, and reduces the randomness in the optimization process. The hybrid optimization method greatly improves the optimization efficiency, and has been applied to the experiments of the Double-Cone ignition scheme. We believe that it will play a greater role in the future laser fusion experiments.
重要日期
-
会议日期
06月05日
2023
至06月09日
2023
-
04月30日 2023
提前注册日期
-
05月01日 2023
摘要截稿日期
-
05月01日 2023
摘要录用通知日期
-
05月01日 2023
初稿截稿日期
-
05月31日 2023
注册截止日期
主办单位
等离子体物理重点实验室
北京师范大学天文系
北京师范大学天文系
承办单位
Matter and Radiation at Extremes期刊
中国工程物理研究院流体物理研究所
北京应用物理与计算数学研究所
中国工程物理研究院流体物理研究所
北京应用物理与计算数学研究所
联系方式
- Contact
- mr******@aip.org
- +86********
历届会议
-
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2019年05月29日 中国 Hefei
第四届极端物质与辐射国际会议 -
2017年06月01日 中国 Beijing,China
第二届极端物质与辐射国际会议
