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在高功率微波介质窗外表面周围, 气体击穿是限制功率容量提升的主要因素之一, 因而进行相应的模拟研究具有重要的意义. 本文通过粒子-蒙特卡洛碰撞模型对介质窗气体侧击穿特性进行了模拟研究. 将宏粒子合并方法引入该模型, 大大减少了跟踪的宏粒子数量, 以至于能够对整个击穿过程进行模拟与分析. 结果表明, 在宏粒子权重为变量下, 击穿的时空演化特性与宏粒子权重为常数下的结果吻合得很好. 由于次级电子发射产额远小于1, 所以气体电离是介质窗气体侧击穿的主导机理. 电子电离和扩散导致等离子体的密度和厚度随着时间显著增加. 电子密度的峰值未出现在介质表面处而是在距离介质表面100—150 μm的位置. 这是因为大量的电子沉积在介质表面上, 伴随产生的自组织法向电场驱使电子远离介质表面. 由于本文关注的背景气体压强高于最大电离率对应的临界压强(约为10 Torr), 所以 电离率随着压强的增加而单调地减小, 并导致击穿发展得更加缓慢. 通过比较击穿时间的模拟值与实验数据, 证实了粒子-蒙特卡洛碰撞模型的准确性.
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关键词:
- 气体击穿 /
- 介质表面 /
- 高功率微波 /
- 粒子-蒙特卡洛碰撞模型 /
- 宏粒子合并方法
Gas breakdown is one of the key factors restricting the increase of power capacity around the outer surface of high-power microwave dielectric window. It is of great significance to conduct corresponding simulation studies. Compared with the fluid model, the particle-in-cell-Monte Carlo collision model has two advantages: firstly, the influence of numerical dispersion and instability problems is insignificant; secondly, it can accurately describe microphysical processes. Therefore, the breakdown characteristics on gas side of dielectric window are simulated by the particle-in-cell-Monte Carlo collision model. The two-in-one macro-particle merging method is introduced into the model, which greatly reduces the number of macro-particles tracked, so that the whole breakdown process can be simulated and analyzed. The results show that the spatial and temporal evolution of breakdown under the variable macro-particle weight is in good agreement with that under the constant macro-particle weight. This suggests that the two-in-one macro-particle merging method is applicable under the simulation conditions of interest in this paper, i.e., when the ratio of the effective electric field of microwaves to the pressure is between $1.76\times10^3$ and $1.41\times10^4$ V/(m$\cdot$Torr). Since the yield of secondary electron emission is much less than 1, gas ionization is the dominant mechanism of breakdown on gas side of dielectric window. Electron ionization and diffusion lead to a significant increase in the density and thickness of the plasma over time. The peak of electron density does not appear at the dielectric surface, but at a position 100–150 μm away from the dielectric surface. This is because a large number of electrons are deposited on the dielectric surface, and the accompanying self-organized normal electric field drives the electrons away from the dielectric surface. Since the background gas pressure of interest in this paper is higher than the critical pressure corresponding to the maximum ionization rate (about 10~Torr), the ionization rate decreases monotonically with increasing pressure and leads to a slower development of breakdown. The accuracy of the particle-in-cell-Monte Carlo collision model is confirmed by comparing the simulated values of breakdown time with experimental data. This work provides an important theoretical basis for understanding and controlling the breakdown on gas side of dielectric window. The following figure (a) shows that the mean electron energy under the variable macro-particle weight agrees well with that under the constant macro-particle weight at 100~Torr. The following figure (b) shows that using the particle-in-cell-Monte Carlo collision model with a two-in-one macro-particle merging method allows the breakdown process to be considered when the plasma density increases by a factor of $10^8$.
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Keywords:
- Gas breakdown /
- dielectric surface /
- high-power microwave /
- particle-in-cell-Monte Carlo collision model /
- macro-particle merging method
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图 1 高功率微波作用下介质窗气体侧击穿的示意图
Fig. 1. Schematic diagram of breakdown on gas side of dielectric window of high power microwave.
图 2 在背景气体压强为100 Torr和宏粒子权重分别为变量与常数下, (a)平均电子能量, 微波电场以及(b)电子数量随时间的变化
Fig. 2. The change of (a) mean electron energy, microwave electric field, and (b) number of electrons over time with the macro-particle weights as variables and constant, respectively. The background gas pressure is 100 Torr in this figure.
图 3 在背景气体压强为100 Torr和宏粒子权重分别为变量与常数下, $ t=2.5\; $ns时的电子数密度随坐标z的变化
Fig. 3. The variation of electron number density with coordinate z at time $ t=2.5 $ ns when the weights of macro–particles are variables and a constant, respectively. The background gas pressure is 100 Torr in this figure.
图 4 在背景气体压强为100 Torr和宏粒子权重分别为变量与常数下, 代表电子的宏粒子数量随时间的变化
Fig. 4. The variation of the number of macro–particles representing electrons over time when the weights of macro–particles are variables and a constant, respectively. The background gas pressure is 100 Torr in this figure.
图 5 背景气体压强为100 Torr下电子密度$ n_\mathrm{d} $随时间和空间的变化
Fig. 5. The variation of electron density $ n_\mathrm{d} $ with time and space under background gas pressure of 100 Torr.
图 6 背景气体压强为100 Torr下带电粒子密度和自组织法向电场$ E_\mathrm{n} $在$ t=7 $ ns时的空间分布
Fig. 6. Spatial profiles of charged particle density and self-organizing normal electric field $ E_\mathrm{n} $ at time $ t=7 $ ns under background gas pressure of 100 Torr.
图 7 背景气体压强分别为50, 100和200 Torr下电子数量随时间的变化
Fig. 7. Change in the number of electrons over time under background gas pressures of 50, 100 and 200 Torr.
图 8 电离率与 次级电子发射产额关于时间的平均值$ \nu_{\mathrm{av}} $和$ \delta_{\mathrm{av}} $随背景气体压强的变化
Fig. 8. The average values $ \nu_{\mathrm{av}} $ and $ \delta_{\mathrm{av}} $ of ionization rate and secondary electron emission yield with respect to time as a function of background gas pressure.
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