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The effects of database parameter uncertainty on uranium(VI) equilibrium calculations

FRANK H. DENISON and JACQUELINE GARNIER-LAPLACE
Geochimica et Cosmochimica Acta, Vol. 69, No. 9, pp. 2183–2191

Document type > *Article de revue

Keywords > radiological protection, database, ENVIRHOM (programme), uncertainty, uranium

Research Unit > IRSN/DEI/SECRE/LRE

Authors > GARNIER-LAPLACE Jacqueline

Publication Date > 06/03/2005

Summary

The propagation of database parameter uncertainty has been assessed for aqueous and mineral equilibrium calculations of uranium by Monte Carlo and quasi-Monte Carlo simulations in simple inorganic solution compositions. The concentration output distributions of individual chemical species varies greatly depending on the solution composition modelled. The relative uncertainty for a particular species is generally reduced in regions of solution composition for which it is predicted to be dominant, due to the asymptotic behaviour imposed by the mass balance constraint where the species concentration approaches the total element concentration. The relative uncertainties of minor species, in regions where another species comprising one or several of the same components is predicted to be dominant with a high probability, also appear to be reduced slightly. Composition regions where two or several species are equally important tend to produce elevated uncertainties for related minor species, although the uncertainties of the major species themselves tend to be reduced. The non-linear behaviour of the equilibrium systems can lead to asymmetric or bimodal output distributions; this is particularly evident close to equivalence points or solubility boundaries.
Relatively conservative estimates of input uncertainty can result in considerable output uncertainty due to both the complexity of uranium solution chemistry and the system interdependencies. The results of this study suggest that for some modelling scenarios, “classical” speciation calculations based on mean value estimates of the thermodynamic values may result in predictions of a relatively low probability compared to an approach that considers the effects of uncertainty propagation.

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