Comparison of Mo versus W for Double Shell Target Capsules using Machine Learning Optimization

Double shell targets are an alternative ignition platform for inertial confinement fusion [1]. The inner shell materials of interest for double shell targets are molybdenum and tungsten. Molybdenum has a lower density that could produce a more stable implosion, while tungsten has a higher density that could provide more compression and radiative trapping. Currently, there has not been enough comparison between optimized designs for these two inner shell materials. Our previous work has focused on developing a multi-fidelity Bayesian optimization framework to find yield optimized double shell target geometries [2,3,4]. In this work, we apply the multi-fidelity Bayesian optimization to find optimal, or near optimal, double shell targets with molybdenum and tungsten inner shells for a 1.25 MJ laser drive using “pre shot” xRAGE simulations [5]. The optimized targets for each inner shell material are compared to better understand the physics driving the implosion. Analysis of the simulations used in the study show trends in designs that contribute to high yields, ion temperatures, and fuel areal densities.

References

[1] D. Montgomery, et al., “Design considerations for indirectly driven double shell capsules,” Physics of Plasmas 25, 092706 (2018).

[2] N. Vazirani, et al. “Coupling 1d xrage simulations with machine learning for graded inner shell design optimization in double shell capsules,” Physics of Plasmas 28, 122709 (2021).

[3] N. Vazirani, et al. "Coupling multi-fidelity xRAGE with machine learning for graded inner shell design optimization in double shell capsules." Physics of Plasmas 30.6 (2023).

[4] N. Vazirani, et al. "Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design." Statistical Analysis and Data Mining: The ASA Data Science Journal 17.3 (2024): e11698.

[5]M. Gittings, et al. “The RAGE Radiation-Hydrodynamic Code,” Computational Science Discovery 1 (2008), https://doi.org/10.1088/1749-4699/1/1/015005.