Number of the records: 1

Data assimilation in early phase of radiation accident using particle filter

SYSNO ASEP	0331546
Document Type	C - Proceedings Paper (int. conf.)
R&D Document Type	Conference Paper
Title	Data assimilation in early phase of radiation accident using particle filter
Title	Asimilace v časné fázi radiační nehody pomocí particle filteru
Author(s)	Hofman, Radek (UTIA-B)_RID Šmídl, Václav (UTIA-B)_{RID, ORCID} Pecha, Petr (UTIA-B)_{RID, ORCID}
Source Title	The Fifth WMO International Symposium on Data Assimilation. - Melbourne : Australian Government - Bureau of Meteorology, 2009 / Kepert Jeffrey D.
Pages	s. 1-8
Number of pages	8 s.
Publication form	www - www
Action	The Fifth WMO International Symposium on Data Assimilation
Event date	05.10.2009-09.10.2009
VEvent location	Melbourne
Country	AU - Australia
Event type	WRD
Language	eng - English
Country	AU - Australia
Keywords	data assimilation ; particle filter ; prediction ; cloud shine ; Gaussian puff ; dose rate ; reactor accident ; decision support
Subject RIV	DL - Nuclear Waste, Radioactive Pollution ; Quality
R&D Projects	1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
	GA102/07/1596 GA ČR - Czech Science Foundation (CSF)
	GP102/08/P250 GA ČR - Czech Science Foundation (CSF)
CEZ	AV0Z10750506 - UTIA-B (2005-2011)
Annotation	Exploitation of the data assimilation methodology in the field of radiation protection is studied. When radioactive pollutants are released into the atmosphere, a radioactive plume is passing over the terrain. In order to ensure efficiency of introduced countermeasures, it is necessary to predict spatial and temporal distribution of the aerial pollution and material already deposited on the ground. The predictions are made by the means of numerical dispersion models with many inputs. A group of the most significant input parameters affecting the dispersion process was selected using available sensitivity and uncertainty studies performed on dispersion models. Exact values of these parameters are uncertain due to the stochastic nature of atmospheric dispersion, hence the parameters are modeled as random quantities. We attempt to estimate these parameters upon measurements using particle filter. The algorithm is tested on an artificial scenario.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2010

Number of the records: 1