Simulations on the multi-shell target ignition driven by radiation pulse in Z-pinch dynamic hohlraum*

Chen, Shi-Jia; Ma, Yunlong; Wu, Feiyang; Yang, Xiaohu; Yuan, Yun; Cui, Yun; Ramis, Rafael

doi:10.1088/1674-1056/ac01c2

Cited by 3 publications

(1 citation statement)

References 39 publications

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“…The code MULTI-IFE is used to determine the implosion performance driven by a given laser pulse under spherical symmetry approximation. MULTI-IFE is the onedimensional version of the radiation hydrodynamic program MULTI [27][28][29][30][31], which is used widely in the community of inertial fusion [32][33][34] and high-energy-density physics [35].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Laser Pulse for Double-cone Ignition via Machine Learning

Song

Yang

2022

Preprint

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Double-cone ignition (DCI) scheme is a promising fast-ignition approach for the realization of inertial fusion energy. The optimization of laser pulse plays a key role for the fuel compression required by the high gain fusion burning. In this paper, we employ the genetic algorithm in machine learning to optimize the laser pulse in couple with one-dimensional hydrodynamic simulations for the fuel compression. It is found that quantum degeneracy is beneficial for the achievement of high density compression. Analysis from the dataset indicates that the areal density is strongly proportional to the peak density and implosion velocity. Numerical results also suggest that a peak density of 1000 g/cm 3 and an areal density of 3 g/cm 2 could be achieved with a drive energy of 300 kJ in the configuration of double-cone ignition scheme.

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Section: Introductionmentioning

confidence: 99%

Optimization of Laser Pulse for Double-cone Ignition via Machine Learning

Song

Yang

2022

Preprint

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A two-layer single shell magnetized target for lessening the Nernst effect

Chen,

Wu,

Zhang

et al. 2024

Nucl. Fusion

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Fuel magnetization significantly lowers the required radial convergence enabling cylindrical implosions to become an promising approach for inertial confinement fusion (ICF). Nernst effect on the two-layer single shell magnetized target design applied to Z-pinch benefits from a gold layer that decreases fuel demagnetization and serves as a magnetothermal insulation layer, preventing magnetothermal losses. The resistive diffusion and Nernst advection of the magnetic field are considered in the radiation magnetohydrodynamic (RMHD) model, which alter the evolution of magnetic flux in the magnetized target and result in plasma demagnetization. The results demonstrate that targets with a wide range of parameters can achieve ignition condition under a 30 MA driven current. A two-layer single shell magnetized target for lessening the Nernst effect has the potential to achieve ignition condition. The fusion yield of the optimal target increases by 168% from 0.71 MJ to 1.90 MJ, compared to a one-layer single shell target.

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Two-dimensional radiation hydrodynamic simulations of high-speed head-on collisions between high-density plasma jets

Yang¹,

Wu²,

Chen³

et al. 2022

Acta Phys. Sin.

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Collisions of plasma jets are common hydrodynamic phenomena in astrophysical and laser-plasma interaction processes. Deriving scaling relationships between colliding plasmas and initial conditions of plasma jets is of great significance for the optimization design and data analysis of the relevant experiments. Double-Cone Ignition (DCI) scheme is an excellent platform for the study of plasma jets collision, since the collision of high-speed, high-density plasma jets can be easily generated and characterized in both simulations and experiments. In this paper, we employ the upgraded two-dimensional arbitrary Eulerian-Lagrange (ALE) program MULTI-2D to simulate collision process of plasma jets with high speed (≥ 100 km/s) and high density (≥ 10 g/cc). Using the database obtained from the simulations, hydrodynamic scaling laws that describing the collision process of plasma jets are derived with the Bayesian inference method in machine learning. The Bayesian inference method not only has the parameter estimation function of traditional least square method, but also has other potential advantages such as giving the probability distribution of estimated parameters. Numerical results show that the collision of plasma jets with open boundaries is easy to form an isochoric plasma distribution with high-density. Increasing the initial density and velocity of the plasma jets is helpful to enhance the density and temperature of the colliding plasmas. Increasing the initial temperature of plasma jets is beneficial to achieve colliding plasmas with a higher temperature, while leading to a decreased plasma density and pressure after collision. When the initial density, temperature and velocity of the plasma jets are set to be 15 g/cc, 30 eV and 300 km/s, respectively, the colliding plasma density can reach more than 300 g/cc. This is very favorable for the following fast electron heating process in the double-cone ignition (DCI) scheme. The issue about quantum degeneracy after collision is discussed in this work. Under the typical initial conditions of plasma jets in DCI scheme (100km/s ≤V0≤500km/s, 10eV ≤T0≤ 100eV, 10g/cc ≤ρ0≤ 50g/cc, both quantum degenerate plasma and classical non-degenerate plasma can be obtained with the temperature between 0.3TF (Fermi temperature) and 3TF. By comparing the plasma temperature and Fermi temperature of the collision, the criterion for achieving quantum degenerate plasma or non-degenerate plasma under given initial conditions is obtained with the help of the derived hydrodynamic scaling laws. The criterion shows that higher initial velocity, higher temperature and lower density of plasma jets are required if we want to obtain non-degenerate plasma after collision.

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Simulations on the multi-shell target ignition driven by radiation pulse in Z-pinch dynamic hohlraum*

Cited by 3 publications

References 39 publications

Optimization of Laser Pulse for Double-cone Ignition via Machine Learning

Optimization of Laser Pulse for Double-cone Ignition via Machine Learning

A two-layer single shell magnetized target for lessening the Nernst effect

Two-dimensional radiation hydrodynamic simulations of high-speed head-on collisions between high-density plasma jets

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