聚变粒子排气系统中稀薄气体流动的确定性和随机建模

C. Tantos, S. Varoutis, C. Day
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引用次数: 6

摘要

本文首次采用确定性方法对核聚变装置粒子排气系统中的稀薄气体流动进行了模拟。以具有几何复杂度高、宏观量梯度强等特点的DEMO (DEMOnstration Fusion Power Plant)核聚变反应堆抽运区为例。该体系的克努森数可以从自由分子到滑移状态变化,流动行为必须用玻尔兹曼方程来描述。在本工作中,玻尔兹曼方程由著名的Bhatnagar-Gross-Krook和Shakhov动力学模型和确定性离散速度方法进行近似。此外,为了评估确定性建模的能力,还利用随机直接模拟蒙特卡罗(DSMC)方法求解Boltzmann方程进行了研究。在实际意义上的所有宏观量,即压力、数量密度、温度和泵送通量方面,对确定性方法和随机方法进行了扩展比较,并对所实现的确定性方法的有效性进行了评论。通过假设He和D2气体流量、不同的抽气口俘获系数值以及两种不同的进口气体温度情景,得到了结果。在所有检测的情况下,确定性结果与DSMC的结果非常吻合,最大相对偏差小于4%。在可接受的噪声水平下,非线性确定性码明显快于随机DSMC码。用捕获系数计算了泵送通量和泵送口附近的压力值,这两个量对泵送系统的评价都是有用的。本文的工作可为DEMO抽水技术的适用性和抽水系统的设计提供决策支持。
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Deterministic and stochastic modeling of rarefied gas flows in fusion particle exhaust systems
In the present work, a deterministic approach is applied for the first time ever to simulate the rarefied gas flow in the particle exhaust system of a nuclear fusion device. As an example of such a system, the pumping area of the DEMO (DEMOnstration Fusion Power Plant) fusion reactor is considered, which is characterized by high geometrical complexity and strong gradients of macroscopic quantities. The Knudsen number in this system may vary from free molecular up to the slip regime and the flow behavior must be described by the Boltzmann equation. In the present work, the Boltzmann equation is approximated by the well-known Bhatnagar–Gross–Krook and Shakhov kinetic models supplemented with the deterministic discrete velocity method. In addition, in order to assess the capabilities of the deterministic modeling, the problem has also been studied by solving the Boltzmann equation with the stochastic direct simulation Monte Carlo (DSMC) method. Extended comparisons between the deterministic and stochastic methods in terms of all macroscopic quantities of practical interest, namely, pressure, number density, temperature, and pumping fluxes, are performed and remarks about the effectiveness of the implemented deterministic approach have been drawn. Results are obtained by assuming He and D2 gas flows, various values of the capture coefficient at the pumping opening, and two different scenarios of the inlet gas temperature. In all examined cases, the deterministic results are in very good agreement with the DSMC ones, with the maximum relative deviation being less than 4%. The nonlinear deterministic code is significantly faster than the stochastic DSMC code for acceptable noise levels. The pumping fluxes and the pressure values in the vicinity of the pumping opening, both quantities useful for pumping system evaluation, have been calculated in terms of the capture coefficient. The present work may support decision making on the suitability of the pumping technology of DEMO and the design of the pumping system.
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