Abstract
A number of recent studies have been devoted to the estimation of errors of reactor calculation parameters by the GRS (Generation Random Sampled) method. This method is based on direct sampling input data resulting in formation of random sets of input parameters which are used for multiple calculations. Once these calculations are performed, statistical processing of the calculation results is carried out to determine the mean value and the variance of each calculation parameter of interest. In our study this method is used for estimation of errors of calculation parameters (K{sub eff}, power density, dose rate) of a perspective sodium-cooled fast reactor. Neutron transport calculations were performed by the nodal diffusion code TRIGEX and Monte Carlo code MMK. (authors)
Highlights
Evaluation of calculation errors due to uncertainties of neutron data and technological parameters has become one of the important problems of reactor physics
The well-known approach to solve this problem is based on the use of sensitivity coefficients (e.g. Ref. [1]) of reactor calculation parameters of interest to the input data
The main advantage of this approach is that small computational times are necessary
Summary
Evaluation of calculation errors due to uncertainties of neutron data and technological parameters (geometrical and material data) has become one of the important problems of reactor physics. It is based on random sampling sets of input calculation data (neutron cross sections, geometrical and material data) and multiple recalculations of the reactor calculation parameters of interest. This gives sets of statistically distributed values for each calculation parameter. In this paper the GRS technique is applied to estimate uncertainties of calculation parameters, such as Keff, power density and stainless steel dose rate, of a perspective sodium-cooled fast reactor These uncertainties are due to uncertainties of neutron cross sections and other input parameters of the reactor calculation model (geometrical and material data). In the case of Keff, the results obtained with the GRS technique are compared with those obtained with the sensitivity approach
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