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A Preliminary Investigation of the Applicability of Surface Complexation Modeling to the Understanding of Transportation Cask Weeping

Published online by Cambridge University Press:  25 February 2011

Victoria E. Granstaff
Affiliation:
Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-0342
William B. Chambers
Affiliation:
Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-0342
Daniel H. Doughty
Affiliation:
Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-0342
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Abstract

A new application for surface complexation modeling is described. These models, which describe chemical equilibria among aqueous and adsorbed species, have typically been used for predicting groundwater transport of contaminants by modeling the natural adsorbents as various metal oxides. Our experiments suggest that this type of modeling can also explain stainless steel surface contamination and decontamination mechanisms.

Stainless steel transportation casks, when submerged in a spent fuel storage pool at nuclear power stations, can become contaminated with radionuclides such as 137Cs, 134Cs, and 60Co. Subsequent release or desorption of these contaminants under varying environmental conditions occasionally results in the phenomenon known as “cask weeping.” We have postulated that contaminants in the storage pool adsorb onto the hydrous metal oxide surface of the passivated stainless steel and are subsequently released (by conversion from a fixed to a removable form) during transportation, due to varying environmental factors, such as humidity, road salt, dirt, and acid rain. It is well known that 304 stainless steel has a chromium enriched passive surface layer; thus its adsorption behavior should be similar to that of a mixed chromium / iron oxide.

To help us interpret our studies of reversible binding of dissolved metals on stainless steel surfaces, we have studied the adsorption of Co+2 on Cr2O3. The data are interpreted using electrostatic surface complexation models. The FITEQL computer program was used to obtain the model binding constants and site densities from the experimental data. The MINTEQA2 computer speciation model was used, with the fitted constants, in an attempt to validate this approach.

Type
Articles
Copyright
Copyright © Materials Research Society 1994

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References

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