首页 | 本学科首页   官方微博 | 高级检索  
     


Optimizing the spatial pattern of networks for monitoring radioactive releases
Authors:S.J. Melles,G.B.M. HeuvelinkC.J.W. Twenhö  fel,A. van DijkP.H. Hiemstra,O. BaumeU. Stö  hlker
Affiliation:a Environmental Sciences Group, Wageningen University, P.O. Box 47, 6700 AA, Wageningen, The Netherlands
b National Institute for Public Health and the Environment, The Netherlands
c University of Utrecht, Department of Physical Geography, P.O. Box 80.115, 3508 TC, Utrecht, The Netherlands
d Federal Office for Radiation Protection, Bundesamt für Strahlenschutz, Germany
Abstract:This study presents a method to optimize the sampling design of environmental monitoring networks in a multi-objective setting. We optimize the permanent network of radiation monitoring stations in the Netherlands and parts of Germany as an example. The optimization method proposed combines minimization of prediction error under routine conditions with maximizing calamity detection capability in emergency cases. To calculate calamity detection capability, an atmospheric dispersion model was used to simulate potentially harmful radioactive releases. For each candidate monitoring network, we determined if the releases were detected within one, two and three hours. Four types of accidents were simulated: small and large nuclear power plant accidents, deliberate radioactive releases using explosive devices, and accidents involving the transport of radioactive materials. Spatial simulated annealing (SSA) was used to search for the optimal monitoring design. SSA was implemented by iteratively moving stations around and accepting all designs that improved a weighted sum of average spatial prediction error and calamity detection capability. Designs that worsened the multi-objective criterion were accepted with a certain probability, which decreased to zero as iterations proceeded. Results were promising and the method should prove useful for assessing the efficacy of environmental monitoring networks designed to monitor both routine and emergency conditions in other applications as well.
Keywords:Spatial simulated annealing   Radioactive plumes   Radiation   Prediction error variance   Geostatistics
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号