The blind implosion-maker: Automated inertial confinement fusion experiment design
The blind implosion-maker: Automated inertial confinement fusion experiment design
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DOI：
10.1063/1.5091985
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发表时间：
2019-06-01
影响因子：
2.2
通讯作者：
Scott, R. H. H.
中科院分区：
文献类型：
--
作者：
Hatfield, P. W.;Rose, S. J.;Scott, R. H. H.
惯性约束聚变(ICF)实验的设计，以及能量密度物理理论和实验方法的发展，是寻求将核聚变作为一种可行的能源的关键挑战之一。先生。717,012005(2016年)]。最近在国家点火设施(NIF)实现高当量内爆方面的挑战导致了人们对考虑比通常研究的更广泛的设计参数空间产生了新的兴趣[J.L.Peterson等，Phys。等离子体24,032702(2017年)]。在这里，我们报告了一种算法方法，可以产生合理的ICF设计与最小的假设。特别是，我们使用了遗传算法元启发式算法，其中模拟了内爆群体，胶囊的设计由基因组描述，自然选择消除了糟糕的设计，高质量的设计基于产量相互交配，设计经历了突变以引入新的想法。我们证明了该算法需要类似于5x10(4)的模拟才能找到原始的NIF设计。我们还将该方法与设计过程的其他部分联系起来，展望了一种完全自动化的ICF实验设计过程-将ICF从实验设计问题转变为算法设计问题。
The design of inertial confinement fusion (ICF) experiments, alongside improving the development of energy density physics theory and experimental methods, is one of the key challenges in the quest for nuclear fusion as a viable energy source [O. A. Hurricane, J. Phys.: Conf. Ser. 717, 012005 (2016)]. Recent challenges in achieving a high-yield implosion at the National Ignition Facility (NIF) have led to new interest in considering a much wider design parameter space than normally studied [J. L. Peterson et al., Phys. Plasmas 24, 032702 (2017)]. Here, we report an algorithmic approach that can produce reasonable ICF designs with minimal assumptions. In particular, we use the genetic algorithm metaheuristic, in which populations of implosions are simulated, the design of the capsule is described by a genome, natural selection removes poor designs, high quality designs are mated with each other based on their yield, and designs undergo mutations to introduce new ideas. We show that it takes similar to 5x10(4) simulations for the algorithm to find an original NIF design. We also link this method to other parts of the design process and look toward a completely automated ICF experiment design process-changing ICF from an experiment design problem to an algorithm design problem.