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Parametrization of homogeneous forested areas and effect on simulated dose rates near a nuclear research reactor
Journal of Environmental Radioactivity ( IF 2.3 ) Pub Date : 2020-10-23 , DOI: 10.1016/j.jenvrad.2020.106445
Gunther Bijloos , Johan Camps , Lise Tubex , Johan Meyers

One of the major uncertainties in dispersion-based simulations at the local scale is the representation of terrain effects. The aim of the current study is to quantify this type of uncertainty for dose-rate predictions over a homogeneous forest cover. At the Belgian reactor BR1, situated in a forested environment, ambient gamma-dose-rate data from routine Ar-41 releases are available in the first 300 m from the release point. We develop a forest parameterization that meets the site-specific needs, and integrate it in different dispersion models. Using different terrain-roughness parameterizations, we compare three types of models: a dispersion model driven by a Langevin equation, an advection-diffusion model, and a Gaussian plume model as a special case of the latter one. We find that all models are biased up to a factor of four, partly due to an uncertain source strength. The dose-rate uncertainty due to the model choice is a factor of 2.2 for a stack release and a factor of 14 for a ground release.



中文翻译:

均质林区的参数化及其对核研究堆附近模拟剂量率的影响

局部尺度上基于色散的模拟的主要不确定性之一是地形效应的表示。当前研究的目的是对均匀森林覆盖率的剂量率预测进行量化。在处于森林环境中的比利时反应堆BR1处,从释放点开始的前300 m,可获得常规Ar-41释放的环境伽马剂量率数据。我们开发了满足站点特定需求的森林参数化,并将其集成到不同的分散模型中。使用不同的地形粗糙度参数化,我们比较了三种类型的模型:由Langevin方程驱动的色散模型,对流扩散模型和高斯羽状模型作为后者的特例。我们发现所有模型的偏差最多为四分之一,部分是由于不确定的光源强度。由于模型选择而导致的剂量率不确定性对于烟囱释放来说是2.2倍,对于地面释放来说是14倍。

更新日期:2020-10-30
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