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Original title:
Bayesian Methods for Optimization of Radiation Monitoring Networks
Authors: Šmídl, Václav ; Hofman, Radek
Document type: Research reports
Year: 2011
Language: eng
Series: Research Report, volume: 2315
Abstract: Release of radioactive material into the atmosphere is the last possible resort of any accident in a nuclear power plant. It is an extremely rare event, however with severe consequences for potentially many people living in proximity of the power plant. Awareness of radiation security has been increased after the Chernobyl accident, and almost every country is now equipped with monitoring network of on-line connected receptors continually measuring radiation levels. Initial configurations of the network were designed by experts using their experience.In this report, we are concerned with local scale modeling of less severe accident in the range of tens of kilometers from the nuclear power plant. Both the stationary and mobile groups will be discussed. The preferred model of uncertainty is the empirical density which will be assimilated with measurements using the sequential Monte Carlo methodology. We will discuss influence of various loss functions.
Keywords: data assimilation; radiation monitoring; UAV
Project no.: VG20102013018 (CEP)
Funding provider: GA MV
Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2012/AS/smidl-bayesian methods for optimization of radiation monitoring networks.pdf
Original record: http://hdl.handle.net/11104/0212208
Permalink: http://www.nusl.cz/ntk/nusl-126817
The record appears in these collections:
Research > Institutes ASCR > Institute of Information Theory and Automation
Reports > Research reports
Authors: Šmídl, Václav ; Hofman, Radek
Document type: Research reports
Year: 2011
Language: eng
Series: Research Report, volume: 2315
Abstract: Release of radioactive material into the atmosphere is the last possible resort of any accident in a nuclear power plant. It is an extremely rare event, however with severe consequences for potentially many people living in proximity of the power plant. Awareness of radiation security has been increased after the Chernobyl accident, and almost every country is now equipped with monitoring network of on-line connected receptors continually measuring radiation levels. Initial configurations of the network were designed by experts using their experience.In this report, we are concerned with local scale modeling of less severe accident in the range of tens of kilometers from the nuclear power plant. Both the stationary and mobile groups will be discussed. The preferred model of uncertainty is the empirical density which will be assimilated with measurements using the sequential Monte Carlo methodology. We will discuss influence of various loss functions.
Keywords: data assimilation; radiation monitoring; UAV
Project no.: VG20102013018 (CEP)
Funding provider: GA MV
Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2012/AS/smidl-bayesian methods for optimization of radiation monitoring networks.pdf
Original record: http://hdl.handle.net/11104/0212208
Permalink: http://www.nusl.cz/ntk/nusl-126817
The record appears in these collections:
Research > Institutes ASCR > Institute of Information Theory and Automation
Reports > Research reports
Record created 2012-11-02, last modified 2023-12-06