Reliability Engineering & System Safety
Response surfaces and sensitivity analyses for an environmental model of dose calculations
Introduction
The radiological impact evaluation of the nuclear facilities is one of the great challenge of the nuclear industry. Radiological exposure models due to severe nuclear accident or due to chronic releases have been extensively developed. In such complex models, it was recognized that many input variables are largely uncertain and that a rigorous procedure is required to arrive at realistic uncertainty distributions. Recently, uncertainty analysis techniques have been used in consequences investigation of different severe nuclear accident models [1], [2], [3], [4].
This paper is devoted to the presentation of a global sensitivity analysis of a French radiological impact software called GASCON. GASCON is dedicated to chronic atmospheric releases and dosimetric impact, and is used for CEA facilities safety assessment. This software evaluates the doses received by a population (called reference group) exposed to the cloud of radionuclides and via the food ingestion pathways. It takes into account the interactions which exist between the man, the plant and the animal, the different pathways of transfer (wind, ), the distance between emission and observation, the time passed between emission and .
Various stages in the analysis of a process (software, measurement, ) introduce potential errors, in particular, in the construction of the various models: real phenomenon with the physical model, physical model with the mathematical model, and mathematical model with the numerical model. The principal sources of uncertainties are in the approximation made by the modeling of the physical phenomenon, the approximations made on the parameterization of the model, the input data and the input parameters. The uncertainty analysis is used to evaluate the confidence interval or the probability distribution of the result. The global sensitivity analysis is used to quantify the influence of the input parameters uncertainties on the output variables uncertainties [5], [6]. Recent studies have applied different methods of uncertainty and sensitivity analysis to environmental models for the radioactive waste management problem [7], [8].
The results provided by GASCON are in the form of annual effective doses (Sv/year) received by a reference group, divided into three age compartments: adult, child and baby. We also distinguish three operating cycles of the gas release: one year, 10 years, 50 years. In our study the reference group is a village near the nuclear facility, and we consider two radionuclides 129I and 238U. There is thus 18 output variables. The main ways of exposure taken into account in GASCON are:
external exposures: radioactive cloud, soil deposits, groundshine;
internal exposures: plume inhalation, ingestion of plants contaminated by direct pathway (foliar transfer by contact with the radioactive cloud) and indirect pathway (soil deposit then root transfer), ingestion of contaminated animal productions (animals having eaten plants contaminated by direct and indirect pathways).
dose factors for external irradiation, effective ingestion, effective inhalation;
transfer factors to animal productions (milk, meat of cow, ewe, goat, );
factors of soil–plant transfer (vegetables, cereals, );
translocation factors (fruits, vegetables, );
sorption coefficients (sands, silts, clays and organic matter);
dry deposition velocity for each radionuclide;
local feed rations of the reference group for the various age compartments (vegetables, fruits, cereals, milk, meat, ), and animal feed rations (grass, hay, corn) related to the products eaten by the reference group.
The following section presents the four steps of our methodology: uncertainty analysis via Monte-Carlo calculations, sensitivity analysis by computations of correlation coefficients between input and output variables, construction of response surfaces requiring negligible computation times, final sensitivity analysis by calculations of Sobol sensitivity indices. In the third section this methodology is applied to the GASCON software using specific nuclear facility and reference group. We conclude this study with a summary in the last section.
Section snippets
Uncertainty analysis
The general objective of an uncertainty analysis is to evaluate uncertainty on a computation result Y taking into account uncertainties on the input parameters . To do so, it is necessary to evaluate a probability density function for each input parameter (by expert opinion or by data statistical analysis). The results of the uncertainty analysis is conditioned with the choices of these probability densities. To propagate uncertainties, we use a simple Monte-Carlo strategy [9], [10]
Results
The GASCON software has been applied to a particular facility on Cadarache, a French nuclear research center. The reference group is the population of a village, distant of a few kilometers of this facility. The gas release (129I and 238U) is fixed at a symbolic value of 1 Bq/year which does not represent a realistic release. This also induces nonrealistic effective dose rates. Three operating cycles are studied: one year, 10 years, and 50 years.
Conclusion
The four steps of our methodology (Monte-Carlo simulation, correlation coefficients analysis, response surfaces construction, Sobol indices calculation) have allowed to quantify the influence of input parameters on the GASCON software response (annual effective dose received by the man), for a specific nuclear facility, a specific population, and for two radionuclides (129I and 238U). During the correlation coefficient analysis, the calculations of standardized rank regression coefficients and
Acknowledgements
This work was supported by the MRIMP project of the “Risk Control Domain” which depends on CEA/Nuclear Energy Division/Nuclear Development and Innovation Division. We are grateful to P. Guetat (CEA/DAM/DASE) for providing the GASCON software.
References (26)
- et al.
Uncertainty and sensitivity analysis of early exposure results with the MACCS reactor accident consequence model
Reliab Eng Syst Saf
(1995) - et al.
Uncertainty and sensitivity analysis of food pathway results with the MACCS reactor accident consequence model
Reliab Eng Syst Saf
(1995) - et al.
Uncertainty and sensitivity analysis of chronic exposure results with the MACCS reactor accident consequence model
Reliab Eng Syst Saf
(1995) - et al.
Sensitivity analysis of an environmental model: an application of different analysis methods
Reliab Eng Sys Saf
(1997) Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal
Reliab Eng Syst Saf
(1993)Probabilistic dose calculations and sensitivity analyses using analytical models
Reliab Eng Syst Saf
(2003)- et al.
Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems
Reliab Eng Syst Saf
(2003) - et al.
A methodology for fitting and validating metamodels in simulation
Europ J Oper Res
(2000) Non parametric variance-based methods of assessing uncertainty importance
Reliab Eng Syst Saf
(1997)Making best use of model evaluations to compute sensitivity indices
Comput Phys Commun
(2002)