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Implementation and Validation of the Hydride Nucleation-Growth-Dissolution (HNGD) model in BISON
Journal of Nuclear Materials ( IF 2.8 ) Pub Date : 2020-11-22 , DOI: 10.1016/j.jnucmat.2020.152683
Florian Passelaigue , Evrard Lacroix , Giovanni Pastore , Arthur T. Motta

During the operation of a light water reactor, a fraction of the hydrogen produced by waterside corrosion is absorbed into the nuclear fuel cladding. When the hydrogen concentration reaches its solubility limit, a brittle zirconium hydride phase precipitates, leading to a loss of ductility of the cladding. To assess cladding integrity, an accurate simulation tool is needed to predict hydrogen distribution within the cladding and hydride precipitation. Recent studies have developed an improved understanding of the physical processes involved in hydrogen redistribution, and hydride precipitation and dissolution. This research led to the development of a new model, called Hydride Nucleation-Growth-Dissolution (HNGD). The present work describes the implementation of HNGD into the fuel performance code BISON, developed at Idaho National Laboratory. The main innovative feature of the HNGD model is that it accounts for hydride nucleation and growth as two distinct precipitation components, using the Johnson-Mehl-Avrami-Kolmogorov model to describe hydride growth kinetics. Each step of the model implementation into BISON was systematically verified, and simulations of experiments performed for validation, showing that the HNGD model provides improved predictions, and captures some experimentally observed physical phenomena related to hydride growth that the previous model could not.



中文翻译:

BISON中氢化物成核-生长-溶解(HNGD)模型的实现和验证

在轻水反应堆的运行过程中,水边腐蚀产生的一部分氢气被吸收到核燃料包壳中。当氢浓度达到其溶解度极限时,易碎的氢化锆相析出,导致覆层的延展性降低。为了评估包层的完整性,需要一种精确的模拟工具来预测包层内的氢分布和氢化物沉淀。最近的研究对与氢再分布以及氢化物沉淀和溶解有关的物理过程有了更好的理解。这项研究导致开发了一种新模型,称为氢化物成核-生长-溶解(HNGD)。本工作将HNGD的实现描述为爱达荷州国家实验室开发的燃油性能代码BISON。HNGD模型的主要创新特征是,它使用Johnson-Mehl-Avrami-Kolmogorov模型描述了氢化物的生长动力学,从而将氢化物的成核和生长解释为两个不同的沉淀成分。系统验证了将模型实施到BISON中的每个步骤,并进行了实验仿真以进行验证,结果表明HNGD模型提供了改进的预测,并捕获了一些实验观察到的与氢化物生长有关的物理现象,而以前的模型则无法做到。

更新日期:2020-11-22
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