Gellenoncourt Allan, Ayoub Ali, Wainwright Haruko M
Institut National des Sciences et Techniques Nucléaires, Cadarache, France.
Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, USA.
Sci Rep. 2025 Apr 7;15(1):11914. doi: 10.1038/s41598-025-95571-0.
This paper presents a new strategy to optimize radiation monitoring networks for effectively predicting contaminated areas and radiation levels during nuclear power plant accidents in order to improve emergency response efforts. Our strategy addresses variable metrological fields by generating ensemble simulations of wind fields and radionuclide migration in the atmosphere using the WSPEEDI (Worldwide version of System for Prediction of Environmental Emergency Dose Information) simulator. GPCAM (Gaussian Process for Continuous-time Acquisition of Measurements) is then used to capture the heterogeneity of radiation levels by sparse monitoring points, and to optimize their locations. We consider three different scenarios: (a) a single static spatial distribution of the radiation levels, (b) the temporal evolution of the distribution within a single release scenario for mobile sensor deployment, and (c) ensemble optimization with variable metrological conditions for assessing risks and emergency responses at a particular site a priori. The results are compared with the homogeneously-distributed network. Our results show that GPCAM is able to identify effective monitoring locations for each of these scenarios, except that a prevailing wind direction is required for the ensemble case. In addition, we compare the effect of different acquisition functions, kernel functions, and hyperparameters in GPCAM on the sensor locations.
本文提出了一种优化辐射监测网络的新策略，以便在核电站事故期间有效预测污染区域和辐射水平，从而改进应急响应工作。我们的策略通过使用WSPEEDI（全球环境应急剂量信息预测系统版本）模拟器生成风场和大气中放射性核素迁移的集合模拟，来应对多变的气象场。然后，利用GPCAM（连续时间测量获取的高斯过程）通过稀疏监测点捕捉辐射水平的异质性，并优化其位置。我们考虑了三种不同的情景：(a)辐射水平的单一静态空间分布，(b)移动传感器部署的单一释放情景内分布的时间演变，以及(c)在特定地点先验评估风险和应急响应的具有可变气象条件的集合优化。将结果与均匀分布的网络进行比较。我们的结果表明，GPCAM能够为这些情景中的每一种确定有效的监测位置，只是集合情景需要主导风向。此外，我们比较了GPCAM中不同采集函数、核函数和超参数对传感器位置的影响。
