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Assessment of semi-mechanistic bubble departure diameter modelling for the CFD simulation of boiling flows

机译:半机械气泡离开直径建模对沸腾流体CFD模拟的评估

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Eulerian-Eulerian two-fluid computational fluid dynamic (CFD) models are increasingly applied to predict multiphase and boiling flows in nuclear reactor thermal hydraulics. In these models, nucleate boiling is usually accounted for by partitioning the heat flux between the different mechanisms of heat transfer involved. Although structured in a mechanistic fashion, heat flux partitioning models are still forced to rely on mainly empirical closure relations. Between the numerous closures required, the bubble departure diameter in particular has a significant influence on the predicted interfacial area concentration and void distribution within the flow. There is now abundant evidence in the literature of the limited accuracy and reliability of the empirically-based correlations that are normally applied in CFD models. In view of this, in this work more mechanistic formulations of bubble departure have been introduced into the STAR-CCM + code. The models are based on a balance of the hydrodynamic forces that act on a bubble at the nucleation site. Their performance, and compatibility with existing implementations in a CFD framework, are assessed against two different data sets for vertically upward subcooled boiling flows. In general, a significant number of modelling choices is required by these mechanistic models and some recommendations are made. The models are extended to include a more physically-consistent coupled calculation of the frequency of bubble departure. In general, predictions of the wall temperature reach a satisfactory accuracy, even if numerous numerical and modelling uncertainties are still present. In view of this, several areas for future work and modelling improvement are identified, such as the proper modelling of the local subcooling acting on the bubble cap.
机译:欧拉-欧拉两流体计算流体动力学(CFD)模型正越来越多地用于预测核反应堆热工水力中的多相和沸腾流动。在这些模型中,成核沸腾通常是通过在涉及的不同传热机制之间分配热通量来解决的。尽管以机械方式构造,但热通量分配模型仍被迫主要依靠经验闭合关系。在所需的多个封闭之间,气泡离开的直径尤其会对预测的界面面积浓度和流中的空隙分布产生重大影响。现在,在文献中有大量证据表明,通常在CFD模型中应用的基于经验的相关性的准确性和可靠性有限。有鉴于此,在这项工作中,更多的气泡脱离机制被引入了STAR-CCM +代码中。这些模型基于作用在成核部位气泡上的流体动力的平衡。针对垂直向上过冷沸腾流的两个不同数据集,评估了它们的性能以及与CFD框架中现有实现的兼容性。通常,这些机械模型需要大量的建模选择,并提出了一些建议。这些模型被扩展为包括气泡离开频率的物理一致性更强的耦合计算。通常,即使仍然存在许多数值和模型不确定性,对壁温的预测也能达到令人满意的精度。有鉴于此,确定了未来工作和建模改进的几个领域,例如作用于气泡帽的局部过冷的正确建模。

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