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Modelling of multidimensional effects in thermal-hydraulic system codes under asymmetric flow conditions – Simulation of ROCOM tests 1.1 and 2.1 with ATHLET 3D-Module
Nuclear Engineering and Technology ( IF 2.7 ) Pub Date : 2021-04-24 , DOI: 10.1016/j.net.2021.04.015
E. Diaz Pescador , F. Schäfer , S. Kliem

The implementation and validation of multi-dimensional (multi-D) features in thermal-hydraulic system codes aims to extend the application of these codes towards multi-scale simulations. The main goal is the simulation of large-scale three-dimensional effects inside large volumes such as piping or vessel. This novel approach becomes especially relevant during the simulation of accidents with strongly asymmetric flow conditions entailing density gradients. Under such conditions, coolant mixing is a key phenomenon on the eventual variation of the coolant temperature and/or boron concentration at the core inlet and on the extent of a local re-criticality based on the reactivity feedback effects. This approach presents several advantages compared to CFD calculations, mainly concerning the model size and computational efforts. However, the range of applicability and accuracy of the newly implemented physical models at this point is still limited and needs to be further extended. This paper aims at contributing to the validation of the multi-D features of the system code ATHLET based on the simulation of the Tests 1.1 and 2.1, conducted at the test facility ROCOM. Overall, the multi-D features of ATHLET predict reasonably well the evolution from both experiments, despite an observed overprediction of coolant mixing at the vessel during both experiments.



中文翻译:

非对称流动条件下热工液压系统代码中的多维效应建模——使用 ATHLET 3D 模块模拟 ROCOM 测试 1.1 和 2.1

热工液压系统代码中多维(多维)特征的实现和验证旨在将这些代码的应用扩展到多尺度模拟。主要目标是模拟大体积(如管道或容器)内的大型三维效果。这种新颖的方法在模拟具有密度梯度的强烈不对称流动条件的事故期间变得尤为重要。在这种情况下,冷却剂混合是冷却剂温度和/或堆芯入口处硼浓度最终变化以及基于反应性反馈效应的局部再临界程度的关键现象。与 CFD 计算相比,这种方法具有几个优点,主要涉及模型大小和计算工作量。然而,新实现的物理模型在这一点上的适用范围和准确性仍然有限,需要进一步扩展。本文旨在基于对测试设施 ROCOM 进行的测试 1.1 和 2.1 的模拟,为验证系统代码 ATHLET 的多维特征做出贡献。总体而言,尽管在两个实验期间观察到容器中冷却剂混合的高估,但 ATHLET 的多维特征相当好地预测了两个实验的演变。

更新日期:2021-04-24
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