Radiation Protection Bureau, Health Canada, 775 Brookfield Road, Ottawa, Canada; Belgian Nuclear Research Institute, Boeretang 200, Mol, Belgium; Royal Meteorological Institute of Belgium, Ringlaan 3, Brussels, Belgium.
Radiation Protection Bureau, Health Canada, 775 Brookfield Road, Ottawa, Canada.
J Environ Radioact. 2020 Jul;218:106225. doi: 10.1016/j.jenvrad.2020.106225. Epub 2020 Mar 10.
Atmospheric transport and dispersion models are important tools in radiation protection as they help to estimate the impact of radionuclides released into the atmosphere. In particular, such models can be used in combination with radionuclide observations to estimate unknown source term parameters, or to improve source term estimates obtained through other methods. In this paper, a Bayesian inference system was used to determine the source term parameters and their corresponding credible intervals of a real-world anomalous Se release at a nuclear facility in Belgium. Furthermore, a formulation is proposed that not only takes into account true detections, but also true instrumental non-detections, false alarms and real misses. The Bayesian inference system is able to correctly determine the known source location. The Bayesian inference is then refined by fixing the release location and by making stronger assumptions about the release period.
大气迁移和扩散模型是辐射防护中的重要工具，因为它们有助于估计放射性核素释放到大气中对环境的影响。特别是，此类模型可与放射性核素观测结果结合使用，以估算未知源项参数，或改进通过其他方法获得的源项估算。在本文中，使用贝叶斯推理系统来确定比利时核设施中实际异常硒释放的源项参数及其相应的可信区间。此外，还提出了一种公式，该公式不仅考虑了真实检测，还考虑了真实的仪器未检测、误报和真实遗漏。贝叶斯推理系统能够正确确定已知的源位置。然后，通过固定释放位置并对释放期做出更强的假设，对贝叶斯推理进行了细化。
