High to Low pellet cladding gap heat transfer modeling methodology in an uncertainty quantification framework for a PWR Rod Ejection Accident with best estimate coupling

IF 0.9 Q3 NUCLEAR SCIENCE & TECHNOLOGY
G.-K. Delipei, J. Garnier, J. L. Pallec, B. Normand
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引用次数: 2

Abstract

High to Low modeling approaches can alleviate the computationally expensive fuel modeling in nuclear reactor’s transient uncertainty quantification. This is especially the case for Rod Ejection Accident (REA) in Pressurized Water Reactors (PWR) were strong multi-physics interactions occur. In this work, we develop and propose a pellet cladding gap heat transfer (Hgap) High to Low modeling methodology for a PWR REA in an uncertainty quantification framework. The methodology involves the calibration of a simplified Hgap model based on high fidelity simulations with the fuel-thermomechanics code ALCYONE1. The calibrated model is then introduced into the CEA developed CORPUS Best Estimate (BE) multi-physics coupling between APOLLO3 R © and FLICA4. This creates an Improved Best Estimate (IBE) coupling that is then used for an uncertainty quantification study. The results indicate that with IBE the distance to boiling crisis uncertainty is decreased from 57% to 42%. This is reflected to the decrease of the sensitivity of Hgap. In the BE coupling Hgap was responsible for 50% of the output variance while in IBE it is close to 0. These results show the potential gain of High to Low approaches for Hgap modeling in REA uncertainty analyses.
具有最佳估计耦合的压水堆堆棒抛射事故的不确定性量化框架中高到低球团包层间隙传热建模方法
从高到低的建模方法可以减轻核反应堆暂态不确定性量化中燃料建模的计算成本。压水堆堆棒抛射事故是一种强多物理场相互作用的事故。在这项工作中,我们开发并提出了一种在不确定性量化框架下的压水堆REA的颗粒包层间隙传热(Hgap)高到低建模方法。该方法包括使用燃料热力学代码ALCYONE1对基于高保真度模拟的简化Hgap模型进行校准。然后将校正后的模型引入CEA开发的APOLLO3 R©与FLICA4之间的CORPUS Best Estimate (BE)多物理场耦合。这创建了一个改进的最佳估计(IBE)耦合,然后用于不确定性量化研究。结果表明,使用IBE后,沸点危机不确定性距离从57%降低到42%。这反映在Hgap的灵敏度降低上。在BE耦合中,Hgap负责50%的输出方差,而在IBE中,它接近于0。这些结果显示了在REA不确定性分析中Hgap建模的从高到低方法的潜在增益。
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来源期刊
EPJ Nuclear Sciences & Technologies
EPJ Nuclear Sciences & Technologies NUCLEAR SCIENCE & TECHNOLOGY-
CiteScore
1.00
自引率
20.00%
发文量
18
审稿时长
10 weeks
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