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作 者:Tao Tao Guannan Zheng Qing Jia Rui Yan Jian Zheng
机构地区:[1]Department of Plasma Physics and Fusion Engineering and CAS Key Laboratory of Geospace Environment,University of Science and Technology of China,Hefei,China [2]Department of Modern Mechanics,University of Science and Technology of China,Hefei,China [3]Collaborative Innovation Center of IFSA,Shanghai Jiao Tong University,Shanghai,China
出 处:《High Power Laser Science and Engineering》2023年第3期76-85,共10页高功率激光科学与工程(英文版)
基 金:supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDA25010200);the Fundamental Research Funds for the Central Universities (No. WK2140000014);the DCI joint team
摘 要:Pulse shaping is a powerful tool for mitigating implosion instabilities in direct-drive inertial confinement fusion(ICF).However,the high-dimensional and nonlinear nature of implosions makes the pulse optimization quite challenging.In this research,we develop a machine-learning pulse shape designer to achieve high compression density and stable implosion.The facility-specific laser imprint pattern is considered in the optimization,which makes the pulse design more relevant.The designer is applied to the novel double-cone ignition scheme,and simulation shows that the optimized pulse increases the areal density expectation by 16%in one dimension,and the clean-fuel thickness by a factor of four in two dimensions.This pulse shape designer could be a useful tool for direct-drive ICF instability control.
关 键 词:double-cone ignition hydrodynamics instability machine-learning optimization pulse shape optimization
分 类 号:TL62[核科学技术—核技术及应用]
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