高保真与中保真程序卵石层速度剖面的比较
Comparison of Pebble Bed Velocity Profiles Between High-Fidelity and Intermediate-Fidelity Codes
摘要：
最近的兴趣，高温气体反应堆的发展增加了需要更先进的理解在随机填充卵石床的流动特性。正确理解这些流动特性可以更好地了解系统在正常运行和事故情况下的冷却能力。为了提高计算效率的准确性，中间保真度建模，高保真度模拟可以用于生成相关数据。在这项研究中，NekRS，一个GPU支持的光谱元素计算流体动力学代码，用于产生高保真的流动数据的床1,568和45,000卵石。爱达荷国家实验室的Pronghorn多孔介质代码被用作中间保真度代码。高保真模型的结果被分成多个同心区域，以提取每个区域中的孔隙度和速度平均值。将孔隙度值输入Pronghorn模型，并将所得速度剖面与NekRS的速度剖面进行比较。这两种情况下运行的雷诺数为20,000基于卵石直径。Pronghorn结果被发现显着高估的速度在最外面的区域，表明单独的孔隙度的变化不会导致流体速度的差异。我们的结论是，进一步的工作是必要的，以开发一个更有效的阻力系数相关的近壁区，提高预测能力的中间保真度模型。
英文摘要：
Recent interest for the development of high-temperature gas reactors has increased the need for more advanced understanding of flow characteristics in randomly packed pebble beds. A proper understanding of these flow characteristics can provide a better idea of the cooling capabilities of the system in both normal operation and accident scenarios. In order to enhance the accuracy of computationally efficient, intermediate fidelity modeling, high-fidelity simulation may be used to generate correlative data. For this research, NekRS, a GPU-enabled spectral-element computational fluid dynamics code, was used in order to produce the high-fidelity flow data for beds of 1,568 and 45,000 pebbles. Idaho National Lab's Pronghorn porous media code was used as the intermediate fidelity code. The results of the high-fidelity model were separated into multiple concentric regions in order to extract porosity and velocity averages in each region. The porosity values were input into the Pronghorn model and the resulting velocity profile was compared with that from NekRS. Both cases were run with a Reynolds number of 20,000 based on pebble diameter. The Pronghorn results were found to significantly overestimate the velocity in the outermost region indicating that changes in the porosity alone do not cause the difference in fluid velocity. We conclude that further work is necessary to develop a more effective drag coefficient correlation for the near-wall region and improve predictive capabilities of intermediate fidelity models.
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